The GRAIT-DM Project

Motivation

Information technology (IT), and specifically ubiquitous wireless connectivity, has provided precious communications during and after the 2011 Tohoku Earthquake. Studies have shown the rapid propagation of very useful information, e.g., the gradual reopening of Tokyo Metro lines during the night of March 11, through social networks such as Twitter.

Big Data Will Support Resilient Critical Infrastructures. With critical infrastructures, such as roads, bridges, and water main networks, cities provide ready and efficient access to facilities and amenities. Careful management is needed to improve the quality of infrastructure systems and their resiliency in face of sudden disasters. The rapid growth of Big Data from both physical sensors and social media in real-time suggests a way to increase efficiency and effectiveness of adaptive resource management techniques. To achieve these goals, we propose the integration of heterogeneous Big Data and real-time analytics to improve the adaptive management of resources when critical infrastructures are under stress.

Objectives

RCN supports for Global Collaborative Research on Real-Time Analytics of Heterogeneous Big Data with Adaptive Management and Use of Resilient Infrastructures.

The main goals of this project are:

  1. the integration of heterogeneous Big Data and real-time analytics that will improve the adaptive management of resources when critical infrastructures are under stress,
  2. the maintenance of a repository of related research, and
  3. the collecting of available public data sets and software tools.

The technologies and tools that arise from RCN-enabled research will be applied to socially and economically impactful areas such as reducing congestion and personalized healthcare in smart cities.

NSF support

The SAVI is primarily funded by National Science Foundation by CNS
(1550379). Any opinions, findings, and conclusions or recommendations
expressed in this material are those of the author(s) and do not necessarily
reflect the views of the National Science Foundation or other funding
agencies and participating companies.