Exploring Emerging Technologies and Concepts to Support Public Safety
How many times in the past few years have you heard the term “historic event” or "unprecedented times?" Probably more than once, and that trend shows no sign of reversing. Natural disasters such as floods, tornadoes, and extreme heat coupled with man-made problems such as ransomware, chemical or biological attacks, and civil disorder can have devastating effects on individuals, communities and entire regions.
Disasters start and end at the local level, and the emergency management community is experiencing a rapidly evolving threat landscape. Driven by this dynamic environment, S&T is using a collaborative, all-hazards approach to support public safety, leveraging new technologies and integrating existing research and development from academic and government institutions.
From artificial intelligence automation to next-generation data management, S&T is working to harness technologies that will better prepare tomorrow's emergency managers.
The emergency management (EM) threat landscape is evolving at an unprecedented pace due to challenges like natural disasters, urbanization, and technological advancements. This shifting landscape requires a dynamic and adaptable approach to EM.
Current EM research and development challenges include:
- Resources for research, development, and innovation (RD&I) to support emergency managers at the state and local level are limited and fragmented across government, academia, and other institutions.
- There is no clear path for systematically transitioning to use the outputs of the nation’s research in the area of emergency management.
- There is no clearly identified lead for emergency management research at the federal government level.
Every great undertaking has to start somewhere and for this, over the past year S&T partnered with Pacific Northwest National Laboratory (PNNL) to execute Emergency Management of Tomorrow Research (EMOTR) to:
- Assess the EM research landscape;
- Assess the artificial intelligence (AI) research landscape;
- Elicit capability needs from EM stakeholders;
- Conduct validation exercises; and
- Identify where technology, such as AI, may benefit the future of Emergency Operation Centers (EOCs).
Together, these efforts navigated the complexities of EM and AI to identify emerging trends, potential challenges, and strategic pathways to guide future investments based on current assessments and projected needs.
To date, EMOTR has identified AI-based technologies with a high probability of enhancing EM in the next decade:
| Highlighted Technologies | Enabling Technologies |
|---|---|
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In addition, the EMOTR validation exercises held in 2024, in combination with findings from the landscape assessments and stakeholder input, resulted in recommendations for a next-generation EOC:
| Concept-Based Recommendations | Supplemental Recommendations |
|---|---|
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What’s Next?
- Roadmaps outlining the feasibility, timing, barriers, and needs for implementation of near-term recommendations.
- Testbeds, operational field assessments, and pilots partnering government, academic, and industry with EM community stakeholders to test emerging technologies.
- Visioning exercises through university challenges to engage the next generation in out-of-the-box thinking.
- Continued stakeholder engagement to enable improved visibility and coordination of EM R&D efforts.
- Flood Resilience
- S&T Impact: Next Generation Emergency Operations
- S&T Impact: Next Generation Emergency Operations (brochure)
- Technology to Reduce the Impacts of Wildfires
For more information about S&T's efforts to address emergency management challenges, contact first.responder@hq.dhs.gov.