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TZID:America/Halifax
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DTSTART:20180311T030000
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BEGIN:VEVENT
DTSTAMP:20190315T005454Z
UID:C3E48BFC-9D9E-4E74-B08D-3BDBDCFA3732
DTSTART;TZID=America/Halifax:20181022T160000
DTEND;TZID=America/Halifax:20181022T170000
DESCRIPTION:In this presentation\, we will focus on the discussion of the c
 oncept of "crowd sensing"\, as an approach to collect data from embedded s
 ensors in smartphones. Its positioning as a first\, inexpensive\, step for
  the building of a collective intelligence makes it a tool that is more an
 d more popular today. This emergent paradigm comes with various applicatio
 ns. However\, many challenges arise given users involvement in the data co
 llection process. In this context\, we will try throughout this presentati
 on to discuss collaborative sensing schemes which tackle the following fou
 r main questions: How to assign sensing tasks to maximize data quality wit
 h energy-awareness? How to minimize the processing time of sensing tasks? 
 How to motivate users to dedicate part of their resources to the crowdsens
 ing process? and How to protect participants privacy and not impact data u
 tility when reporting collected sensory data?\n\nSpeaker(s): Yacine Ghamri
 -Doudane\, \n\nRoom: Slonim Conference Room (#430)\, Bldg: Dalhousie Unive
 rsity\, Goldberg Computer Science Building\, 6050 University Ave\, Halifax
 \, Nova Scotia\, Canada
LOCATION:Room: Slonim Conference Room (#430)\, Bldg: Dalhousie University\,
  Goldberg Computer Science Building\, 6050 University Ave\, Halifax\, Nova
  Scotia\, Canada
ORGANIZER:qye@cs.dal.ca
SEQUENCE:1
SUMMARY:Mobile Crowd Sensing (MCS) - A First Step Towards Building Collecti
 ve Intelligence
URL;VALUE=URI:https://events.vtools.ieee.org/m/179333
X-ALT-DESC:Description: <br /><p><span style="background-color: white\;"><s
 pan style="font-size: small\;"><span style="font-size: 11pt\;">In this pre
 sentation\, we will focus on the discussion of the concept of "crowd sensi
 ng"\, as an approach to collect data from embedded sensors in smartphones.
  Its positioning as a first\, inexpensive\, step for the building of a col
 lective intelligence makes it a tool that is more and more popular today. 
 This emergent paradigm comes with various applications. However\, many cha
 llenges arise given users involvement in the data collection process. In t
 his context\, we will try throughout this presentation to discuss collabor
 ative sensing schemes which tackle the following four main questions: How 
 to assign sensing tasks to maximize data quality with energy-awareness? Ho
 w to minimize the processing time of sensing tasks? How to motivate users 
 to dedicate part of their resources to the crowdsensing process? and How t
 o protect participants privacy and not impact data utility when reporting 
 collected sensory data?</span></span></span></p>
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