Disaster management: How AI can impact risk reduction
August 22, 2018
Artificial intelligence has found its way into helping us make sense of how natural weather phenomena causes disasters and technology helping us find the means to manage its impacts and reduce the risks for harm and danger.
Technology service providers such as IT consulting companies in VA that play critical roles in facilitating the collection of valuable weather and relevant phenomenal data to help authorities address mitigating damaging and traumatic impacts of natural disasters.
Where traditional disaster management failed
Before AI, existing disaster management models were more reactionary and provided data after the fact.
Previous management methods failed to provide real-time data, had very limited capabilities for data collection from multiple sites and unable to recommend preventive or risk-reduction measures.
There have been a lot of cases in the past where the systems failed to mitigate the impacts and the breadth of casualties and damage.
How machine and deep learning tools can optimize disaster management
AI-driven machine and deep learning platforms can leverage on dynamic and robust data from satellite images, historical data, real-time monitoring and hard data from collection agencies located around the world.
All these data are combined in an AI neural network and deep learning algorithms to provide the best available evidence-based solutions.
The AIDR is the winner of the 2016 Open Source Software System Challenge for its unique concept of an open source software that collects data from numerous weather and other data-collection centers and classifies social media posts related to any humanitarian crisis, including natural disasters and calamities.
It leverages on social media channels during crisis situations and AI-driven algorithms kick in to manage the flow of data and other pertinent and verifiable data.
It has been responsible for providing vital information to help address concerns that arise during disasters and has helped coordinate millions of dollars in relief support in disaster-stricken areas around the world.
Banking on AI for Earthquake Response
A California-based start-up is using AI and machine learning to eliminate guesswork in disaster response actions by making accurate predictions about damage caused by earthquakes.
They use up to date data about homes, buildings structures, what materials were used, how were those built and the application of physics to determine the time of a collapse as the earthquake happens. This is followed by environmental data and finally, real-time information such as earthquake magnitude, traffic in the disaster area and weather.
Other tech companies also use similar applications for cyber-attacks, floods, vehicular accidents and other large-scale disasters.
This is how AI technology by IT services, NGO’s, governments and together with other key players in making a difference to improve the conditions of humankind during times of crisis.