Natural disasters are unavoidable and can wreak absolute havoc on cities and towns, regardless if they’re in developing or developed countries. But, what if we had more time to prepare before disaster strikes? And, what if we could predict what areas would suffer the most?
That’s exactly the challenge solved by One Concern. A platform that uses social and economic data as well as AI to uncover a city or town’s weaknesses.
With this hyper-local data, the platform enables policy-makers to make policies before disaster strikes to protect entire cities, vulnerable populations, or “geofence” different segments of society who may be at greater risk. The platform also enables users to make smarter, more informed, quicker decisions, during and after a disaster strikes.
“One Concern gets smarter through ‘collective intelligence’ where human knowledge and expertise is incorporated into the overall platform, enabling AI-driven recommendations to be delivered in real-time,” explains Ben Colombo. “As a result, outcomes on the ground can be changed where lives and livelihoods are protected."
"Outcomes on the ground can be changed where lives and livelihoods are protected."
While the ultimate goal of the platform is to avoid any loss of life, the technology also helps to reduce property damage, business interruption and protect employees.
Behind One Concern’s design, each line of code is a fundamental invention. The team have filed for more than fifteen patents across multiple disciplines of science and technology.
For the past 12 months, the team have tested their technology with promising results. Their model's Seismic Concern and Flood Concern have been successfully trialled in San Francisco, Los Angeles and Seattle as well as the State of Arizona, respectfully.
They’ve also secured new global research partners and built a strong partnership with the World Bank to bring One Concern to developing countries. The first deployment with the World Bank is planned for this year in Dhaka, one of the world’s most disaster-prone cities.