crowd fencing
TRANSCRIPT
A Crowd-‐fencing Network for Disaster Management
Kyoung-‐Sook Kim
Disaster Management: Lifecycle
2
Preparedness Response
Recovery Mi9ga9on
• Scenario developing • Emergency planning/training • Real-‐Ame monitoring • Early warning
• Resource dispatching • SituaAon acquiring • Command control/coordinaAon • InformaAon disseminaAon • Emergency healthcare • Searching and rescuing
• PredicAng hazard • Developing simulaAon model • Risk assessment and mapping • Socio-‐economic and environmental impact assessment
• UpdaAng scenario • SpaAal (re)planning
• Early damage assessment • Re-‐establishing infrastructures (gas, water, telecomm, elect, etc.)
• Medical care • SupporAng seMlement
disaster
Disaster Management: Lifecycle
3
Preparedness Response
Recovery MiAgaAon
• Scenario developing • Emergency planning/training • Real-‐9me monitoring • Early warning
• Resource dispatching • Situa9on acquiring • Command control/coordina9on • Informa9on dissemina9on • Emergency healthcare • Searching and rescuing
• PredicAng hazard • Developing simulaAon model • Risk assessment and mapping • Socio-‐economic and environmental impact assessment
• UpdaAng scenario • SpaAal (re)planning
• Early damage assessment • Re-‐establishing infrastructures (gas, water, telecomm, elect, etc.)
• Medical care • SupporAng seMlement
disaster
Social Networks
2011 Japanese Experiences • More than 5,500 tweets per second about the disaster • Why the public use social media during disasters:
– Because of convenience – Based on social norms – Based on personal recommendaAons – For humor & levity – For informaAon seeking – For Amely(up-‐to-‐date) informaAon – For unfiltered informaAon – To determine disaster magnitude – To check in with family & friends – To self-‐mobilize – To maintain a sense of community – To seek emoAonal support & healing
1) CommunicaAon tools 2) InformaAon resources to gain situaAonal awareness 3) Monitoring and Response tools for emergency managers
Reasons of NOT Using Social Media
5
hMp://swfound.org/media/119739/IAC-‐13.E5.5.3_NA.pdf
• Privacy and security fears • Accuracy concerns • Access issues • Knowledge deficiencies
* LimitaAons of current social media (network) 1) Too much informaAon in a non-‐visual format. 2) Not enough interac9ve content. 3) No (or not enough) emphasis on sharing 4) Human-‐centric message format 5) Passive acAvity
Crowd-‐fencing Networks
Monitor
Iden9fy
Assess
Control
Geo-‐Fencing & Crowd-‐Sourcing integraAon Parents can get the noAficaAon when their child enters or leaves a dangerous or a defined area via SMS or Email
the process of obtaining needed services, ideas, or content from a large group of people, and especially from an online community
monitoring
delivering delivering
monitoring
predicAng adjusAng
Cloud CompuAng
smart phone
server
database
Mobile/PC
Crowd-‐fencing Networks
hospital
medical device
CCTV
traffic signal
ambulance
satellite
person
Billions of Internet-‐enabled
devices
Real-‐Ame informaAon sharing
Social systems
Cloud resources
Infrastructures
portable/wearable sensors and actuators
Challenges
• ScienAfic and technical challenges – IntegraAng complex, heterogeneous large-‐scale systems
– InteracAon between humans and systems
– Dealing with uncertainty – Measuring and verifying system performance
– System design
• InsAtuAonal, societal, and other challenges – Trust, security, and privacy – EffecAve models of governance
– CreaAon of business models
– MulA-‐disciplinary educaAon and collaboraAon
– Skilled workforce
[ref] Strategic R&D OpportuniAes for 21st Century Cyber-‐Physical Systems, hMp://www.nist.gov/el/upload/12-‐Cyber-‐Physical-‐Systems020113_final.pdf
System Requirements • Human factors
– Quality & Reliability • Reviewer • Data provenance management • Trust models • SpaAal and temporal validaAon of data usability
– VisualizaAon à HCI à Explicit and implicit interacAon (sensors & actuators) • Big data handling
– heterogeneous data processing – nonlinear data processing – high-‐dimensional data processing – distributed and parallel data processing
• VirtualizaAon and scalability – On-‐demand resources/services provisioning – migraAon
• Open standards and protocols – Common vocabulary (geolocaAons, events, acAviAes, etc.) – Structured informaAon
• CollecAve intelligence – IncenAve models – Machine learning