ICT in Disaster Management Initiatives in Asia-Pacific Workshop on ICT for Promoting Inclusive and Disaster Resilient Development 14-15 Mai 2015, Ulaanbaatar, Mongolia Christian Wilk metacognition consulting, General Manager
ICT in Disaster Management Initiatives in Asia-Pacific
Workshop on ICT for Promoting Inclusive and Disaster Resilient Development
14-15 Mai 2015, Ulaanbaatar, Mongolia
Christian Wilk
metacognition consulting, General Manager
christian wilk, [email protected]
Key Findings & Main Conclusions
ICTs in DRR and Disaster Management until recently:
– GIS and geospatial information and knowledge management
– Analysis of remote sensed (mostly space-based) imagery and data
– Information management to coordinate people & resources
Innovative Applications:
¬ ICT for Education & Training – Virtual Reality; Games: Thailand (UNESCO)
¬ UAVs (Humanitarian Drones) in disaster management – Nepal (2015), Vanuatu (2015), Philippines (2013), Thailand (2011), China
¬ Crowdsourcing of social media and Internet data – Nepal (2015), Vanuatu (2015), Philippines
¬ Disaster Robotics on the rise – Japan (2011): as conduits & for exploration
christian wilk, [email protected]
ICT in Disaster Management: 4 Phases
¬ Mitigation: Minimizing the effects of disaster
– Examples: building codes and zoning, vulnerability analyses, public education
¬ Preparedness: Planning how to respond – Examples: preparedness plans, emergency exercises and training, early warning
systems
¬ Response: Efforts to minimize the hazards created by a disaster – Examples: search and rescue (robotics), crisis mapping, information management
¬ Recovery: Returning the community to normal state – Examples: temporary housing (rapid prototyping technologies); grants; medical care
christian wilk, [email protected]
ICT in Disaster Management: Main categories
¬ ICT Infrastructure: Augment or replace damaged main communication infrastructure – Examples: mobile, deployable units; TVWS (TV White Space), satellites
¬ Information management – Examples: Sahana, Ushahidi, ArcGIS, Humanitarian ID
¬ Remote Sensing & geospatial information – Examples: Satellite based, Drones, Philippine DOST’s NOAH project
¬ Data analysis using social media and crowdsourcing approaches
¬ Disaster Robotics and Rapid Prototyping
christian wilk, [email protected]
Crowdsourcing & Social Media 1: Overview
¬ What – Community generated data, exchanged on the Internet in online social communities as
pictures, messages and tweets can provide critical information for crisis mapping and
situational awareness building through the analysis of such crowdsourced data
¬ Why – During a disaster, the affected community, response agencies and governments must
all quickly understand who is in need, where they are, what is needed, which agencies
can supply the demand, safe routes, distribution and medical centers etc.
– Crowdsourcing constitutes a quick, efficient, cost-effective and high-quality solution to
this problem
¬ Who – Digital Humanitarian Network DHN
– Humanitarian OpenStreetMap Team HOT
– The Standby Task Force SBTF
– The International Network of Crisis Mappers
christian wilk, [email protected]
Crowdsourcing & Social Media 2: Use Cases
¬ Nepal 2015 – Main objective is to crowdsource the
analysis of tweets and media to rapidly
assess disaster damage and needs
¬ Philippines 2012 and 2013 – In 2012, in response to typhoon Pablo, the
first time a map entirely sourced from
social media analysis was generated.
Within 10 hours more than 20.000 tweets
were analyzed.
christian wilk, [email protected]
Crowdsourcing & Social Media 3: Lessons Learned
¬ Lessons Learned
- Crowdsourced results (categorized messages/ tweets/ pictures; maps) can be
delivered within hours after the event of a disaster
- Issues of reliability and quality can be addressed by having multiple volunteers look at
the same data
- Effective management of large numbers of volunteers has become a problem itself,
but tools to support this have been or are currently developed
- Crowdsourcing in disaster response is still in its early stages, therefore much remains
to be learned, for instance better integration into established disaster response
mechanisms
- Inclusion of local community and diaspora abroad increases the quality of the output
¬ Outlook - Still labour-intensive, requiring a lot of manual input shift to semi-automatic support
using AI techniques such as machine learning/ classification
- Transition from crowdsourced text and image data to other data formats such as 3D,
topographical data in combination with UAVs
christian wilk, [email protected]
UAVs 1: Overview
¬ What – Unmanned aerial vehicles (UAVs, or drones) have been increasingly used for crisis
mapping during disaster response as a replacement for traditional aerial imagery
collected by planes, helicopters or satellites.
¬ Why – UAVs offer a couple of advantages for localized aerial imagery collection or sensing:
quickly deployable, high-resolution sensors, efficient and cost-effective
¬ Who – UAViators
– Drone Adventures
christian wilk, [email protected]
UAVs 2: Use Cases
¬ Nepal 2015 – …
¬ Vanuatu 2015 – …
¬ Philippines 2013 – ....
christian wilk, [email protected]
UAVs 3: Lessons Learned
¬ Lessons Learned
- The biggest challenge remain legal and regulatory provisions (air space, liability,
im-/export).
- Good practices and lessons learned need to be collected, consolidated and shared
- Clear guidelines and a generally accepted code of conduct is needed
- Open issues that need further attention: quality control of UAV pilots, privacy and
data protection of collected data
- Engaging local communities on the use and purpose of UAV missioins is
paramount. UAVs and drones are generally associated with military and surveillance
applications.
¬ Outlook - Interest is growing in using UAVs (equipped with infrared cameras) for search &
rescue
- Cooperation and coordination among a group of UAVs will be possible
- Delivery drones for the supply of medicals and other urgent materials will be the next
step
christian wilk, [email protected]
Disaster Robotics 1: Overview
¬ What – Rescue robots are tactical, organic, unmanned systems that allow emergency
professionals to perceive and act at a distance in real time, also known as having a
remote presence at the disaster site.
¬ Why – Robots make it possible to enter and explore areas that are prohibitive for humans or
other living beings such as search and rescue dogs. Robots can also carry out
important indirect tasks such as acting as a mobile radio beacon or repeater, serving
as a surrogate team member, or shoring a collapse to make it safer for responders.
¬ Who – Center for Robot-Assisted Search and Rescue (CRASAR)
– International Rescue System Institute (IRS)
christian wilk, [email protected]
Disaster Robotics 2: Use Cases
¬ Japan 2011 Use Case – During the Great East Japan Earthquake disaster in 2011, Japanese rescue robots
were used at actual disaster sites for the first time. They were used and tested mainly
along the coastline and at the Fukushima Daiichi nuclear power plant (NPP) to inspect
critical infrastructures, to search for missing persons driven underwater by the tsunami,
to remove debris in the disaster sites, and to inspect buildings that were in danger of
collapsing.
¬ Lessons learned - There was a lack of usable and ready to be deployed robots.
- The biggest issue with disaster robotics and most often cited reason for mission failure
were human interface issues.
- PPP are particularly important
¬ Outlook - Disaster robotics has high theoretical potential, but their use is currently limited by
technical limitations, which – as other areas like UAVs have shown – will be overcome
christian wilk, [email protected]
Recommendations
¬ ICT Infrastructure – Paramount importance remains a functioning, reliable ICT network infrastructure
¬ Awareness raising, Know-how & Technology Transfer – Actively promote and raise awareness of open-source and freely available ICT
solutions in disaster management
¬ Streamlined & harmonized regulations & legal provisions – Develop recommendations for legal and regulatory provisions for the use of automated
platforms like UAVs and disaster robotics
¬ Regional R&D support – Provide support for regional R&D projects and initiatives (financial, organisational,
awareness)
¬ Exchange of Best Practices & Lessons learned – Collect, consolidate and share best practices and lessons learned among countries
and stakeholders