How Big Data Can Help in Disaster Response
With nearly 10,000 people killed and more than 95 million affected, 2017 sadly marked a record-breaking year for natural disasters worldwide, ranging from Hurricane Harvey and the massive earthquake in Mexico to Hurricane Irma and the mudslides in Colombia. Unfortunately, 2018 is turning out to be equally calamitous.
Exacerbated by climate change, the years to come may have even more frequent and higher-impact catastrophes in store. But there is some good news in this disastrous scenario: the proliferation of data analytics and sophisticated technology promises to save lives in the face of disaster. As technology gets smarter, officials and scientists are able to analyze once-untapped information. The field of big-data analytics not only allows predication of disaster paths, but it also enables officials to optimize preparation—mapping evacuation routes, pinpointing flooded areas and formulating rescue strategies, for example. By embracing and analyzing big data, agencies can respond more quickly and effectively to the inevitable.
For better or worse, each disaster provides an enormous amount of data. Mining information from previous disasters, officials and responders can collect insights that help forecast future incidents. Combined with sensor data collection, surveillance and satellite imagery, big data analytics allows mission-critical areas to be surveyed and assessed. Knowing, for example, that a particular area has been flooded, and by how much, provides highly useful benchmarks for mapping out flood-prone zones and planning for where to store key rescue resources nearby—beyond the reach of typical inundation.
Through AI, for instance, Google is predicting flood patterns in India and working to bring greater precision and accuracy to response efforts. Drones are increasingly being used to collect data for contextual mapping when it comes to tackling wildfires. And satellite imagery proved its value when a couple’s plea for help spelled out of logs on their lawn was captured during Hurricane Michael, and the family was rescued.
Similarly, responders can better handle emergencies through the data generated by wearables and personal technology. Information transferred from mobile phone apps, smart watches or connected medical devices can be analyzed to help prioritize response and rescues, for example. When there is an abundance of 911 calls during a disaster, dispatchers can identify callers and make decisions about the urgency of each case based on relevant data, such as age and illnesses.
