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Saving lives with Big Data

In this article, we are going to learn about the saving lives with big data - how big data can help us, what makes this big data platform?
Submitted by Uma Dasgupta, on November 10, 2018

In my previous, articles I have mentioned about applications of big data, also there are many other different exciting applications that are being enabled by big data era.

Our main aim while working with big data is to build methodologies and tools to make big data useful to dynamic data-driven scientific applications. Big data can be implemented in several fields such as areas of science and engineering, including genomics, geoinformatics, metro science, energy management, biomedicine, and personalized health.

Let's discuss some real-life situation where big data is applied and can help us -

Saving lives with Big Data

We come across many firestorms daily all over the world. We cannot control such firestorms by using big data, but something we can do is to get ahead of them by predicting their behavior. This is why disaster management of ongoing wildfires heavily relies on their direction and rate of spread.

As these fires are part of our daily life we can save a lot of lives by applying Big Data.

How big data can help us in this?

A lot of data can be collected from sensors and satellite or other things that can help us to measure environmental factors.

Some data come from organizational data, including area maps, better service updates and filed content databases, which archive how much registers vegetation and other types of fuel are in the way of a potential fire.

What makes this a big data problem?

As I discussed in my previous articles also taking out value from big data is our main objective. This is the main aim behind all the activities we are doing with big data. If we cannot take out the value from the data and use it then, it is of no use.

So, here in this case also we can predict good responses only if we can integrate this many diverse data stream. This kind of many sources existed for quite some time.

But what is lacking in disaster management today is a dynamic system integration of real-time sensor, networks, satellite imagery, near real-time data management tools, connectivity to the emergency command center and all these before during and after a firestorm.

Most important data sources are sensor data streaming in from weather stations and satellites, such sensed data include image data humidity, air pressure, and we can also include image data streaming from mountaintop cameras and satellites in this category.

A huge part of data is also generated by the public on social media sites, such as facebook, twitter etc. These people generated data are the hardest to streamline during an existing fire, but they can be very valuable once integrated with other data sources. Imagine synthesizing all the pictures on twitter about us ongoing fire or checking the public sentiment around the boundaries of a fire.

Once we have access to such information at our fingertips there are many things we can do with such data.

Let's take a 2nd example, as by analyzing a person’s genetics, his/her environment, daily activities we can detect or predict a health problem early, help prevent disease and in case of illness provide the right drug at the right dose that is suitable just for that particular person. But the main thing is to collect, store, integrate, collaborate and most important to extract value from these data.

Conclusion:

In this article, I discussed several applications of Big data by which we can save a number of lives. We will discuss many other applications of Big data in real life in my upcoming articles. For any queries shoot your questions in the comment section below. See, you in my next article till then stay healthy and keep learning.

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