Location driven computing for real-time situational awareness and humanitarian response

Speaker:  Jibonananda Sanyal – Oak Ridge, TN, United States
Topic(s):  Society and the Computing Profession

Abstract

The world of location enabled big-data has heralded a fundamental shift in how we interact with our surroundings. A large number of our day-to-day activities are being driven by knowledge about how we behave, how we move, how we shop, what we care about, and how we respond in our various interactions. We are sensing the world around us at a rate that has never been done before. The data collected ranges from being unstructured to semi-structured such as geolocated tweets to highly structured, such as satellite observations. Collected data has historically been used to develop inferential and predictive capabilities; however, at this day and age, the volume and velocity of the data has brought about a shift in how we use the data to derive insight. 
 
This talk discusses how shifts in the big-data landscape are enabling unprecedented insight. In one application, machine learning and the use of GPU powered high performance computing, including deep-learning, has been applied to identify human settlements for the purposes of humanitarian response. In another application, the talk describes activities during the 2017 hurricane season when real-time situational awareness of the energy sector supported operational emergency preparedness and response.
 
The underlying thesis behind this talk is the increasing availability of data allowing for novel, cost-effective, and efficient approaches for addressing humanitarian needs for meeting emergency situations.

About this Lecture

Number of Slides:  35
Duration:  50 - 60 minutes
Languages Available:  English
Last Updated: 

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