Abstract: The government is unable to estimate the socio-economic status of a remote area and also they are unable to help them. Because the government only has their satellite image as a record and they can only see that area through a map but through this image they cannot get status about that area. So, considering this satellite image of an area, there is a profound need to detect the status of the remote area. In this project, we propose an advanced framework to identify socio-economic status of an area through satellite image. We are considering some major factors or attributes like water supply, rooftops and agriculture landfill and we are going to train some datasets through CNN technique then input satellite image is compare with train datasets and if there is presence of this factors in input image then we classify status of the area as poor, rich or medium.

Keywords: Machine Learning, Malnutrition, CNN, Poverty Prediction

PDF | DOI: 10.17148/IJARCCE.2022.11366

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