---
abstract: 'This is a brief survey of the research performed by Grandata Labs in collaboration with numerous academic groups around the world on the topic of human mobility. A driving theme in these projects is to use and improve Data Science techniques to understand mobility, as it can be observed through the lens of mobile phone datasets. We describe applications of mobility analyses for urban planning, prediction of data traffic usage, building delay tolerant networks, generating epidemiologic risk maps and measuring the predictability of human mobility.'
author:
- |
    Carlos Sarraute[^1,\*^]{} and Martin Minnoni[^1^]{}\
    [[^1^]{}Grandata Labs, San Francisco, CA, USA]{}\
    [[^^]{}Corresponding author: charles@grandata.com]{}\
bibliography:
- '../GD\_works.bib'
title: Brief survey of Mobility Analyses based on Mobile Phone Datasets
---

Introduction
============

The mission of Grandata’s research lab is to improve our understanding of Human Dynamics through the analysis of massive datasets coming from mobile phone companies and other industries. This research has been performed in collaboration with numerous academic groups at MIT, INRIA and ENS Lyon, LNCC, UBA and many others.

We provide here a brief review of our research, intended to serve as an introduction and guideline to the research papers on mobility aspects.

This brief survey focuses on the analysis of mobility in space, investigating the important locations of the users’ trajectories, and how they can be used to infer their participation in large social events. The study of mobility has numerous applications, such as urban planning (Section \[urban-planning\]), data traffic usage prediction (Section \[data-traffic-usage\]), building delay tolerant networks (Section \[delay-tolerant-networks\]), epidemiology (Section \[epidemiology\]), and predictability of human mobility (Section \[mobility-predictability\]).
