co-chairs: robin murphy, texas a&m trevor darrell, university of california berkeley
TRANSCRIPT
Purpose
• 2 day workshop
• Are there fundamental research questions for individual computing disciplines?
• Are there cross-cutting research questions requiring novel, multi-disciplinary solutions?
Importance
• Disasters aren’t increasing, but their impact is– 2000 and 2009 over 7,000 disasters– 1.1 million people casualties worldwide,
affected another 2.5 million directly– loss of $986.7 billion
• Time is Now!– Advances from DoD, social networking,
telecommuting, telemedicine– Need economic resilience– Returning veterans, job creation
Citizens
Insurers
Con-struction
Citizens
Business
InformalStakeholders
Communication of Risk
Social Networking
GIS Mash ups
Unmanned Systems
Damage Models
Wireless Networks
Wireless Networks
GIS Representation Citizen
Science/People as Sensors
Social Networking, People as Sensors
Visualization
Optimization
Embedded Systems
Behavorial Models
Secure Sharing
Computer Vision
Computer Vision
Unmanned Systems
Probabilistic
and Reasoning
Opportunities Increasing
National Guard
Red Cross
National Guard
City Manager
National Guard
National Guard
FEMAFormalStakeholders
Computing for Disasters
Human-Computer Systems
Decision-Making For Extremes Under Extreme Conditions
- Sensemaking, comprehension, and visualization - Trustworthy data- Decision support- Physiological and cognitive impacts
Extreme Complexity- Non-linear, large interdependencies, multiple
temporal and spatial scales, no single optimal solution (“wicked problem”)
- Algorithmic, data complexity- Modeling under uncertainty- Privacy, security- Politics, sociology, psychology, language- Resilience of infrastructure (electrical,
communications, transportation, financial…)
Extreme Scales- Time (before, during, after, real-time, discrete
events vs. climate change…)- Space (local, geographically large, global
impacts…)- Stakeholders (Citizens, government, formal
response agencies, informal response agencies and social media, industry…)
- Data (time, priority, heterogeneity, types, content, sources…)
Computing for Disasters
How… • dynamic socio-technical systems work • stakeholders can comprehend data at
scale• models can be adapted in real-time• to effectively train and educate the
population to exploit technical improvisation
in order to respond to disasters.
5 Unique Directions
1. Integrating computing, physical science, and social science
2. Working and comprehending at scale
3. Real-time Modeling
4. Methods and Metrics
5. Training and Education
Conducts Research Differently
• Is holistic
• Relies primarily on empirical methodologies
• Is based on meaningful partnerships with a stakeholder(s)
Computing Can Revolutionize
• Gathering actionable data• Transmission, transformation, abstraction of
data• Explicit represent and mitigate uncertainty• Social, behavioral and economic
consequences• Optimizing resources and logistics• Reuniting families, identify and triage victims• Training of workers• STEM education and recruitment