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  <title><![CDATA[IPaT Thursday Think Tank: The Unexpected Power of a Barometric Sensor]]></title>
  <body><![CDATA[Research Scientist Bill Eason will lead a discussion on some of the latest&nbsp;Internet of Things (IoT) work within Georgia Tech's Research Network Operations Center. Specifically, he has been working on alternative sensing methods to solve the "urban canyon" problem encountered&nbsp;when using GPS to track Georgia Tech bus movement between&nbsp;midtown highrises. How can we simply use a high-resolution barometric pressure sensor to determine the location of a bus along its route? Can this really be more accurate than GPS? What other ecosystems can we apply such methods to?<p>&nbsp;</p>&nbsp;We will also open&nbsp;the broader,&nbsp;related topic of&nbsp;what might be called "orthogonal inference," where one type of sensor data can be used to infer (apparently) unrelated information. Whether it's a single&nbsp;data stream by itself, or aggregated streams from various sources, sometimes we're indirectly&nbsp;giving away more information than we might realize.&nbsp;<p><br />&nbsp;</p>]]></body>
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