PhD Dissertation Proposal by Kasthuri JAYARAJAH | Exploiting Mobility for Predictive Urban Analytics & Operations

About The Talk

As cities worldwide invest heavily in smart city infrastructure, it invites opportunities for a next wave of urban analytics. Unlike their predecessors, urban analytics applications and services can now be real-time and proactive -- they can (a) leverage situational data from large deployments of connected sensors, (b) capture attributes of a variety of entities that make up the urban fabric, and (c) use predictive insights to both proactively optimize urban operations and promote smarter policy decisions. With everyday artifacts being increasingly embedded with hardware (e.g., contact-less smart fare cards that people tap-in and out of buses and metro), and due to the sheer uptake of location-based social media platforms in recent years, a wealth of mobility information is being generated at unprecedented rates. Such individual and collective mobility has been long-touted as a key enabler of urban planning studies. This thesis explores how such abundantly available mobility information can be (a) used to understand relationships among people and predict their movement behavior, (b) integrated with other urban data to provide aggregated insights into demand for urban resources and (c) finally, used to support a more efficient urban sensing infrastructure, to support real-time, proactive urban analytics.

Speaker Biography

Kasthuri JAYARAJAH is a PhD candidate in the School of Information Systems, Singapore Management University, working in the area of mobile and ubiquitous computing. She received her Master in Computing degree from the National University of Singapore, in 2013, and Bachelor of Engineering degree from the University of Moratuwa, Sri Lanka, in 2010. Prior to joining the PhD programme, she was a Research Engineer at the Living Analytics Research Center at SMU. Her current research focuses on exploiting traits of human mobility for urban analytics and situation awareness through the use of physical and social sensing.