CAREER: Data-driven Models of Human Mobility and Resilience for Decision Making
Natural disasters, economic crises, or violent events are some of the shocks that affect many communities every year, forcing them to change their routine behaviors and to quickly adapt to new conditions. Understanding the changes in human mobility patterns and community resilience when shocks take place is critical to design adequate preparedness and response policies. However, decision-makers typically rely on interviews and fieldwork during and after the crises to gain insight information into human reactions, which highly limits the accuracy of their findings. In this proposal, the PI envisions a mobile cyber-physical system (CPS) where people carrying cell phones generate large amounts of metadata that are used to sense, compute and monitor human interactions with the physical environment. Although a lot of work has been done in modeling human behavior under normal circumstances using cell phone metadata, mobility behaviors during shocks are much more complex in nature. As a result, most of the related work is very limited and ad-hoc, lacking any type of serious applicability from a preparedness and response policy perspective. In this CAREER award, the PI proposes to create novel data-driven methods that will reliably characterize and predict human mobility patterns and resilience during shocks so as to improve the development of effective policies. The PI will collaborate with two cell phone carriers to access the cell phone metadata throughout the duration of the award; and with decision-makers from the United Nations to evaluate the proposed methods on three independent five-year, longitudinal studies of periodic shocks: droughts in Haiti; armed conflicts in Colombia; and floods in Bangladesh
Duration:
April 2018 - April 2023
Project Website:
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1750102
Total Award Amount:
$306,388.00