How Satellites and Artificial Intelligence Predict Poverty?
Why Such A Satellite Needs To Be Launched?
Have you ever imagined you’re a twinkling star or a planet. What would you be able to see? What would the world look like through your eyes? How would you be able to figure out the places you have been to? This has happened to all of us, some kids dream of growing up to be scientists, implementing new ideas and technology into people’s lives.
Satellites are also known as the “powerful eyes in the sky”. Rather than sending ordinary satellites into space, the students and researchers from Stanford University School of Earth, Energy & Environmental Sciences have found a way to map poverty in Africa by reading satellite images with the help of artificial intelligence and machine learning.
Instead of manually locating the places where people are struggling to live, this satellite helps in identifying those places which in turn helps the government to help those people at the earliest. If the poverty range is calculated based on the survey, then it might take months or probably years to help those poor and needy people. Whereas the main purpose of the satellite is to save time and money while predicting poverty.
This satellite is launched with artificial intelligence that allows computers to change its algorithm when loaded with new data. The first algorithm was meant to detect poverty in Nigeria, Uganda, Tanzania, Rwanda and Malawi.
"I think the goal is to understand the world much better, in particular the world where a lot of poor people live. And that includes understanding their livelihoods in terms of their sources of income, how their agriculture is performing, how different sectors of the economy perform, and, more specifically, what actually is effective at improving conditions," co-author of the study David Lobell told Mashable in an interview. "All of that is really difficult if you don't have good measurements."
Get To Know How It Predicts Poverty
"There are few places in the world where we can tell the computer with certainty whether the people living there are rich or poor," study co-author Neal Jean, said in a statement. "This makes it hard to extract useful information from the huge amount of daytime satellite imagery that's available."
The tools used for the study are all but simple; initially, scientists used day and night time satellite imagery to identify the brighter part of the country. The concept behind this is that the brighter places use up artificial lightning, which tells us that it is a place where rich people live. Whereas, the dimmer part of the country is what the scientists were targeting. Also, they gave patterns which include road conditions or metal roofs versus thatched roofs.
This study showed its success by proving that it is 81 percent more efficient and effective in predicting poverty. Scientists say that, since the five countries they have tested are more or less similar to each other, they can’t guarantee the success of this method if applied to other countries.
They concluded by saying that the satellite launch was not totally cut off the manual surveys, it was just to make the task easier. Satellite results when combined with manual surveys fulfill the goal of detecting poverty as soon as possible.