Service: Deep Gravity: the algorithm that explains how people move

The traditional model used for the prediction of mobility flows, both on foot and with vehicles, is the so-called "gravitational". Inspired by Isaac Newton's law of universal gravitation, it establishes that the flow of mobility between two places, for example two neighborhoods of a city, is proportional to their population and inversely proportional to their geographical distance.In practice, the gravitational model is often inaccurate because it is based on only two variables, distance and population, and is unable to capture complex relationships between them. The Institute of Science and Information Technologies of the National Research Council (Cnr-Isti) together with the Bruno Kessler Foundation of Trento and the Argonne National Laboratory in the USA, has developed "Deep Gravity", an algorithm that adds to the gravitational model two fundamental ingredients, namely: the use of different variables that describe the points of interest in a place such as restaurants, hotels, hospitals and streets, and the ability to capture complex relationships between these variables thanks to the use of deep learning.