Big Data and Mobility Analytics: What can we learn from the way things (and humans!) move?

Abstract: Things (IoT) will mean that the amount of devices that connect to the Internet will rise massively. This is already giving rise to the creation of massive amounts of data. Spatial and temporal mobility patterns of things and societies as a whole can be characterized based on the interactions that we are able to capture from the IoT sensors.
In this presentation, we will review what we can learn from human mobility patterns, how they can be used to optimize traffic, city planning and tourist attractions. We will review the challenges associated with privacy and security regulation when analyzing mobility patterns. As an application we will present an study on AIS data that describes the locations of vessels traveling in Norwegian seas. We will close the presentation with an overview of the kind of AI techniques we can apply to analyze mobility patterns.

Bio: Arturo Opsetmoen Amador is a senior data scientist working as a consultant for Capgemini. He specializes in the application of AI technologies to solve practical problems that have positive effects on our society. He has experience as a lead data scientist in Smart Digital, a division part of Telenor Norway – Business. He was in charge of bringing the Big Data service «Mobility Analytics» to provide insights into human mobility patterns to the Norwegian market. He has a scientific background and holds a Ph.D. in physics from the Norwegian University of Science and Technology. His interests include Big Data, AI and ML technologies, and how their ethic implementation can improve our society.