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Technologies in Disaster Relief and Rescue Operations

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Chitra Mishra

Natural disasters catalyzed by climate change, extreme weather, and weary & poorly designed infrastructure, among other risks, represent a significant risk to human life and communities. It begins with a death toll figure, which gradually increases as the victims succumb to their injuries waiting for help to arrive. Buried under the debris, or stranded in a flooded property, the injured usually wait it out only to sink deeper into a fatal situation and eventually pass away. These situations call for a quick action or response time and some method that can just pull these stranded lives out of their horror. However, the task of extracting them is not as much a challenge as locating those stranded souls. We have come across and read articles about drones and robots doing the relief work. Lets’ get a little detailed on the how’s and what’s of such technologies.

From apps that we can download on our phones to robots that can be first responders (keeping human emergency personnel safer and freer to do more nuanced tasks), the technology available today can predict & assist in disasters, thereby rapidly reducing the number of deaths and damages. When roads are inaccessible (or people are trapped in difficult to reach situations), drones have become crucial in getting much-needed relief to victims. Drones can deliver medication, food, water,

and provide intel on victims. Some even have devices like defibrillators which can get immediate medical care to those in dire situations - where every second counts in order to prevent brain hemorrhage or death. And getting supplies like antibiotics to people earlier when wounds have become infected in unsanitary conditions can be the difference between keeping or losing a limb. Drones can even deliver blood to those badly hurt. The can go where emergency workers can’t always immediately and that saves lives.

Artificial Intelligence, for instance, can predict the parts of an electrical grid most vulnerable while looking at the data of where a storm is most likely to hit. Result: One, more technician can be deployed to that area, or that they can strengthen or prevent weak areas before it’s too late. Two, IBM’s version is said to be 70 percent accurate in predicting these vulnerabilities as far as 72 hours before a storm hits. People marking themselves safe, is part of an AI enablement. And because of AI’s ability to process and combine large amounts of data intelligently, it can potentially look at untraditional datasets and combine them like Tweets and Facebook posts, large amounts of weather data, and tap into sensors and satellites to get a bigger picture of what’s happening. With that kind of info, it’s easier to come up with the best and most effective ways to help prevent damage and conduct rescues. Being able to evacuate sooner, get to problem areas quicker, and strengthen infrastructure earlier could make AI one of the most powerful tools we have in the fight to keep people safer in natural disasters.

And we’ve only discussed about the rescue operations at the broader level. Is it possible to have something actually deployed in the disaster struck zone that can dig deep and reach the most difficult terrains and extract or identify people at risk. Robots and drones provide abundant and primal benefits for disaster response. They can often fit into places humans can’t, they can operate in environments humans can’t, they can operate continuously without sleep, they can even outperform humans in certain tasks, and most importantly they are replaceable. Robots can be sent places which are too dangerous for human rescue workers, which is often needed in disaster areas.

These first responders would know when entrances and exits are blocked, find other ways in, move rapidly through spaces, and deliver triage faster. Now imagine, if we combined IoT sensor data, social media messages, mobile communications from first responders, and robot exploration of degraded spaces, it will enable such technologies to save more lives faster.

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