HOW BIG DATA ASSISTS IN DISASTER RELIEF AND PREPAREDNESS Posted on : Dec 18 - 2018

Historically, public policies have proved ineffective in providing adequate help for disaster-stricken citizens. A year after hurricane Harvey in 2017, for example, residents are still in the midst of recovery despite $15.3 billion earmarked for relief efforts.

With the emergence of new innovations, one wonders if legislators should give more thought to incorporating Big Data technologies into aiding in disaster prediction and relief.

Over the last two decades, remarkable innovations such as the Internet of things (IoT) have entered the mainstream. While the intensity of natural disasters is increasing, advances in communications because of this technology has greatly reduced casualties and injuries. For instance, agencies such as NASA and the National Oceanic and Atmospheric Administration (NOAA) leveraged big data technology to predict hurricane Harvey’s landfall and coordinate emergency response personnel.

The technology helped the agencies choose ideal disaster response staging locations and evacuation routes as well as pinpoint likely flooding areas and prepare accordingly. Additionally, agencies throughout the storm impact area used machine learning algorithms to dictate the trajectory of the storm and its potential damage.

Big Data for Disaster Management

Big Data technology has proven its merit as a resource for disaster relief and preparedness. It helps emergency responder agencies identify and track populations such as elderly communities or areas with high concentrations of babies and children.

Additionally, Big Data systems help rescue workers identify support resources and plan logistics during emergencies. Big data also facilitates real-time communication during a disaster, and emergency managers use the technology to forecast how residents will react to crises.

Today’s big data systems are growing at an accelerating rate with some studies saying that 90% of the worlds data was created in the last two years. All of this data can be used to help emergency managers make more informed decisions before, during and after natural disasters. View More