Project

AINA: Aerial Imaging and Network Analysis

Groups

This project is aimed at building a machine learning pipeline that will discover and predict links between the visible structure of villages and cities (using satellite and aerial imaging) and their inhabiting social networks. The goal is to estimate digitally invisible villages in India and Sub-Saharan Africa. By estimating the social structure of these communities, our goal is to enable targeted intervention and optimized distribution of information, education technologies, goods, and medical aid. Currently, this pipeline is implemented using a GPU-powered Deep Learning system. It is able to detect buildings and roads and provide detailed information about the organization of the villages. The output will be used to construct probabilistic models of the underlying social network of the village. Moreover, it will provide information on the population, distribution of wealth, rate and direction of development (when longitudinal imaging data is available), and disaster profile of the village.

This project is aimed at building a machine learning pipeline that will discover and predict links between the visible structure of villages and cities (using satellite and aerial imaging) and their inhabiting social networks. The goal is to estimate digitally invisible villages in India and Sub-Saharan Africa. By estimating the social structure of these communities, our goal is to enable targeted intervention and optimized distribution of information, education technologies, goods, and medical aid. Currently, this pipeline is implemented using a GPU-powered Deep Learning system. It is able to detect buildings and roads and provide detailed information about the organization of the villages. The output will be used to construct probabilistic models of the underlying social network of the village. Moreover, it will provide information on the population, distribution of wealth, rate and direction of development (when longitudinal imaging data is available), and disaster profile of the village.