Is this project an undergraduate, graduate, or faculty project?
Undergraduate
Project Type
individual
Campus
Daytona Beach
Authors' Class Standing
Tyler Johnson, Senior
Lead Presenter's Name
Tyler Johnson
Lead Presenter's College
DB College of Aviation
Faculty Mentor Name
Dr. Ryan Wallace
Abstract
The TRANSPORTATION SECURITY ADMINISTRATION / FEDERAL AIR MARSHAL SUAS DETECTION: THREAT INTELLIGENCE & RISK MANAGEMENT PROJECT addresses the emerging safety and security challenges posed by the rapid growth of small Unmanned Aircraft Systems (sUAS) in complex airspace environments. This study analyzed 92 days of sensor-captured Remote Identification (RID) data collected near Fort Lauderdale-Hollywood International Airport (FLL) to assess operational behaviors, aviation risk, and ground risk associated with drone activity. The primary objective of this research is to identify patterns of unauthorized or hazardous sUAS operations to enhance situational awareness and inform actionable risk-mitigation strategies. The analysis identified 335 flights from 150 platforms, dominated almost entirely by DJI models, and utilized geospatial and temporal data to evaluate compliance with existing aviation regulations. Findings indicated that while most operations occurred below 400 feet AGL and at low speeds, many flights exceeded published UAS Facility Map altitudes or operated near historical aircrew-reported sighting locations. Furthermore, the study revealed that flights were typically short-duration and clustered near residential areas or marine facilities, with nearly half of all detected activity occurring within one mile of emergency response infrastructure. These results highlight predictable yet potentially hazardous operational patterns that underscore the critical need for enhanced monitoring and targeted outreach. The significance of this project lies in its ability to provide data-driven insights that strengthen aviation safety and critical infrastructure protection. By codifying these behaviors, the work contributes to the development of refined predictive risk frameworks and improved response protocols for the security community, ultimately supporting the protection of secure airspace and national security interests.
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
Yes, SURF
SMALL UAS DETECTION: THREAT INTELLIGENCE & RISK MANAGEMENT PROJECT
The TRANSPORTATION SECURITY ADMINISTRATION / FEDERAL AIR MARSHAL SUAS DETECTION: THREAT INTELLIGENCE & RISK MANAGEMENT PROJECT addresses the emerging safety and security challenges posed by the rapid growth of small Unmanned Aircraft Systems (sUAS) in complex airspace environments. This study analyzed 92 days of sensor-captured Remote Identification (RID) data collected near Fort Lauderdale-Hollywood International Airport (FLL) to assess operational behaviors, aviation risk, and ground risk associated with drone activity. The primary objective of this research is to identify patterns of unauthorized or hazardous sUAS operations to enhance situational awareness and inform actionable risk-mitigation strategies. The analysis identified 335 flights from 150 platforms, dominated almost entirely by DJI models, and utilized geospatial and temporal data to evaluate compliance with existing aviation regulations. Findings indicated that while most operations occurred below 400 feet AGL and at low speeds, many flights exceeded published UAS Facility Map altitudes or operated near historical aircrew-reported sighting locations. Furthermore, the study revealed that flights were typically short-duration and clustered near residential areas or marine facilities, with nearly half of all detected activity occurring within one mile of emergency response infrastructure. These results highlight predictable yet potentially hazardous operational patterns that underscore the critical need for enhanced monitoring and targeted outreach. The significance of this project lies in its ability to provide data-driven insights that strengthen aviation safety and critical infrastructure protection. By codifying these behaviors, the work contributes to the development of refined predictive risk frameworks and improved response protocols for the security community, ultimately supporting the protection of secure airspace and national security interests.