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WRM: “A Tool for Enabling Anticipatory Thinking in Smart City Planning”

Apr 19, 2017 @ 1:00 pm - 2:30 pm

Muhammad Shahzad
NC State University, CSC


In this talk, I will first give an overview of Anticipatory Thinking. Anticipatory thinking entails preparing in advance for problems and opportunities. It is different from prediction because anticipatory thinking involves preparing for future events instead of simply predicting what might happen. After that, I will describe Futures Wheel, a method to apply anticipatory thinking. Following that, I will describe a tool that we are currently working on that will enable city planners to apply anticipatory thinking in the context of smart cities. Although the development of the tool is at its initial stage, I will present the features that we plan to implement in it. I will also seek feedback and suggestions from the attendees at the talk regarding these features and any other features they might like to see in the tool.

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View Presentation Slides

We are going to use the NC State WebEx for the web conference. Please note that this
WebEx belongs to NC State and can not be downloaded directly from Cisco.
Also, it should work on iPhones and iPads via the WebEx App.
A good internet connection is recommended.
For better audio, please join via computer and then have the meeting call your number
or call in directly using one of the numbers below. When not speaking, please mute
your phone to avoid background noise.
When it’s time, join the WebEx meeting from here:
Meeting Number: 991 680 272
Audio Connection: 919-513-9329 (WolfMeeting)
Access Code: 991 680 272

Sponsored by the Laboratory for Analytic Sciences


Apr 19, 2017
1:00 pm - 2:30 pm
Event Category:
Event Tags:
meeting, research, wednesday, WRM


Partners I Conference 1101
1017 Main Campus Drive
Raleigh, NC 27606 United States
+ Google Map


Mindy Huffman

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LAS aims to bring together a multi-disciplinary group of academic, industry, and government researchers, analysts and managers together to re-engineer the intelligence analysis process to promote predictive analysis. LAS will do this by conducting both classified and unclassified research in a variety of areas of research. The research done in this area will serve as the foundation for mission effects and integrated back into the enterprise.

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