Public safety agencies across the country now have a new resource to help them launch and strengthen their small unmanned aircraft system (sUAS) operations. The Department of Homeland Security’s National Urban Security Technology Laboratory (NUSTL) has published a comprehensive set of recommendations and templates designed to make it easier for fire, police, emergency management, and other public safety agencies to establish drone programs that are safe, standardized, and mission-ready.
The document serves as a practical foundation for agencies at any stage of sUAS development—whether they are starting from scratch or refining an existing program. It outlines the administrative, operational, training, safety, and maintenance elements needed for a successful public safety drone program, and includes ready-to-adapt templates such as policies, procedures, and checklists that can significantly reduce the time and effort typically required to set up these systems.
NUSTL created the guidance in close collaboration with the DHS Big City Fire Working Group (BCF), which represents senior leaders from 13 of the nation’s largest fire departments. Those departments identified a growing need for consistent, scalable documentation to support drone operations—especially as sUAS technologies play an expanding role in emergency response, disaster assessment, search and rescue, hazardous materials incidents, and large-scale events.
As DHS’s only national laboratory dedicated exclusively to supporting state and local first responders, NUSTL focuses on ensuring that public safety professionals have the tools and knowledge they need to prevent, protect against, and respond to homeland security threats. Its mission includes independent testing and evaluation of technologies, helping agencies make informed acquisition and deployment decisions.
The new sUAS documentation package reflects that mission by giving agencies a head start on building programs that comply with best practices, reduce operational risk, and support safe flight operations in demanding environments.
Read the full Documentation here.
(AI was used in part to facilitate this article.)
