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PRODID:IEEE vTools.Events//EN
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DTSTART:20240310T030000
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DTSTART:20231105T010000
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BEGIN:VEVENT
DTSTAMP:20231124T005742Z
UID:D2544171-B383-4DA4-862D-28CA14660795
DTSTART;TZID=America/Chicago:20231116T190000
DTEND;TZID=America/Chicago:20231116T200000
DESCRIPTION:More than 80% of consumer Internet traffic is for videos and mo
 st of them are recorded videos. Meanwhile\, many organizations (such as na
 tional parks\, vacation resorts\, and departments of transportation) provi
 de real-time visual data (images or videos). These videos allow Internet u
 sers to observe events remotely. This speech explains how to discover real
 -time visual data on the Internet. The discovery process uses a crawler to
  reach many web pages. The information on these web pages is analyzed to i
 dentify candidates of real-time data. The data is downloaded multiple time
 s over an extended time period\; changes are detected to determine whether
  it is likely to provide real-time data. The data can be used during an em
 ergency. For example\, viewers may check whether a street is flooded and c
 annot pass. It is also possible to use the data to observe long-term trend
 s\, such as how people react to movement restrictions during the COVID pan
 demic.\n\nSpeaker(s): DR LU\, \n\nVirtual: https://events.vtools.ieee.org/
 m/382713
LOCATION:Virtual: https://events.vtools.ieee.org/m/382713
ORGANIZER:ztaqvi@gmail.com
SEQUENCE:37
SUMMARY:"World-Wide Camera Networks"
URL;VALUE=URI:https://events.vtools.ieee.org/m/382713
X-ALT-DESC:Description: <br /><p>More than 80% of consumer Internet traffic
  is for videos and most of them are recorded videos. Meanwhile\, many orga
 nizations (such as national parks\, vacation resorts\, and departments of 
 transportation) provide real-time visual data (images or videos). These vi
 deos allow Internet users to observe events remotely. This speech explains
  how to discover real-time visual data on the Internet. The discovery proc
 ess uses a crawler to reach many web pages. The information on these web p
 ages is analyzed to identify candidates of real-time data. The data is dow
 nloaded multiple times over an extended time period\; changes are detected
  to determine whether it is likely to provide real-time data. The data can
  be used during an emergency. For example\, viewers may check whether a st
 reet is flooded and cannot pass. It is also possible to use the data to ob
 serve long-term trends\, such as how people react to movement restrictions
  during the COVID pandemic.</p>
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