Reducing disaster impact and rebuilding communities

Citibeats in action. Success story. Natural Disaster Relief.

The new way to reduce disaster impact. @thecitibeats #AI maps not just citizens’ locations but their changing needs during natural disasters.

Natural disasters take lives and devastate communities. From 2004-2013, almost two billion people were directly affected by disaster. And just twenty years ago, the Kobe earthquake in Japan became the world’s most costly disaster ever, with losses totalling over $132 billion. Climate change and increasing industrialization mean natural disasters will continue to increase. Finding ways to mitigate their impact is crucial.

 

Natural disaster relief. Citibeats

 

In a primer on using technology for disaster management, the United Nations Development Program urge “all concerned stakeholders”, from governments to donors to affected organizations, to adopt IT solutions that reduce the impact of storms, hurricanes and other extreme weather. They compare three recent disasters: the Northern Pakistan Earthquake in 2005, the Indian Ocean tsunami in 2004, and the US Hurricane Katrina Katrina in 2005. All three events resulted in a tragic loss of life and damaged the property, infrastructure and economy of the region. But in the case of Katrina, disaster warning and disaster management processes were far more advanced, saving lives and lessening the impact of what could have been an even more devastating catastrophe.

When hazards are planned for, with effective response strategies, “their negative impacts can be mitigated”, the UN report says. And new tech and AI services can provide essential tools that make relief more efficient. Scientific American says that new disaster response technologies will be vital in “saving lives and minimizing damage to infrastructure”. Advance response – like radar devices that forecast storms earlier – must be “paired with better understanding of how to get people to respond to the warnings” to be effective. Innovative solutions that use risk analytics predict weather impact and reduce damage to help both with short-term aid, and with getting communities back on their feet in the long term. These include developments in #Civictech #InsurTech #FinTech and #Proptech – Artificial Intelligence “is one of the fields that have the biggest impact on the insurance industry”, say hackernoon, and this is true for disaster cases where risk analysis and emergency monitoring can help insurers to plan, respond and boost resilience.

For example, real-time mapping technology like MapAction and Open Street Map could “revolutionise disaster response” according to the Guardian. These tools either automatically map areas, or ask citizens or volunteers to provide geomapping data, used to rapidly send resources to where they need to be.  A development partnership blog describes “the power which resides in the crowds to make available what we could call ‘life-saving data’”, highlighting the importance of crowdsourced information and consumer insights to disaster relief.

 

Natural disaster relief. Citibeats

 

Where’s the human perspective in disaster relief?

These developments are inspiring and encouraging. But there are challenges, too. When mapping tools rely on tech alone, they help find routes to affected areas but miss the detailed – and changing – human perspective of what’s needed where and why. When they’re crowdsourced, they rely on the public to be informed and tech-savvy enough to know which tools, systems or apps to use in communicating information.

Citibeats wants to change this. We analyse citizens’ responses to disasters on the social media platforms they ordinarily use for immediate disaster response monitoring. We did a trial run in 2017, teaming up with NTT Data to interpret social media related to natural disasters across three cities in northern Japan: Akita, Aomori and Iwate. Our machine-learning algorithms followed the online conversation and instantly interpreted the data, to show which issues were of most concern.

We found that each city had different priorities. While in Aomori and Iwate access to healthcare was the primary concern, in Aikita, food and mobility were what was needed. Knowing where to focus resources first allows aid to be truly effective, targeted to the needs of the community.

In the weeks following a disaster, the city’s needs evolve and change. Citibeats artificial intelligence monitors the changing conversation, helping to rebuild the community long-term, as some concerns are resolved and new ones emerge. In Aikita, for instance, citizens first needed access to mobility, but in the later aftermath, they began to indicate the damage done to their houses and farmlands that needed fixing.

By hearing what citizens say, city leaders, insurance providers and aid organizations can make better decisions to reduce disaster impact in the short and long term. And looking even further forwards, this detailed record of how disasters impact citizens can even help to predict and prevent disaster damage in the future.

 

Download the full case study for all the details.