BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
DTSTART:20170312T030000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3
TZNAME:EDT
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:20171105T010000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11
TZNAME:EST
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20170226T082035Z
UID:092D8B60-FBFB-11E6-A7C6-0050568D7F66
DTSTART;TZID=America/New_York:20170331T153000
DTEND;TZID=America/New_York:20170331T164500
DESCRIPTION:This is sponsored by the University of Maryland Booz Allen Hami
 lton Distinguished Colloquium Series of the Electrical and Computer Engine
 ering at University of Maryland\, College Park\, and co-sponsored by the I
 EEE Signal Processing Washington Chapter.\n\n"Low-Energy and Flexible GPS 
 Sensing Through Cloud Offloading"\n\nSpeaker: Dr. Jie Liu (Microsoft Resea
 rch -- Redmond\, WA)\n\nCo-sponsored by: UMD ECE Dept. \n\nSpeaker(s): Dr.
  Jie Liu\, \, Dr. Jie Liu\, \n\nAgenda: \n3:15 - 3:30pm: Checking in\n\n3:
 30 - 4:30pm: Lecture by Dr. Jie Liu (Microsoft Research -- Redmond\, WA)\n
 \n4:30 - 5:00pm: Reception (with light refreshment)\n\n"Low-Energy and Fle
 xible GPS Sensing Through Cloud Offloading"\n\nLocation-based services hav
 e become ubiquitous\, thanks to sensors like GPS and RF receivers in our s
 mart phones. However\, the energy consumption of GPS receiving is a major 
 bottleneck for long-term and frequent location sensing. In this talk\, I w
 ill take a deep look into the GPS receiving pipeline and present our effor
 ts on a cloud-offloading approach to GPS-based location sensing. The parti
 tioning between device and cloud brings three kinds of benefits. First\, w
 e can reduce the device side energy consumption by orders of magnitude. Se
 cond\, with the computation power in the cloud\, we can achieve high sensi
 tivity and make GPS receiver work in many indoor places. Finally\, we can 
 leverage opportunistic energy sources on the device side to reduce the amo
 unt of data to be transferred between device and cloud. The cloud-offloadi
 ng architecture help push location sensing and tracking to the next tier o
 f IoT devices.\n\nRoom: 1110\, Bldg: Kim Engineering Building\, University
  of Maryland - College Park\, 8228 Paint Branch Drive\, College Park\, Mar
 yland\, United States\, 20742
LOCATION:Room: 1110\, Bldg: Kim Engineering Building\, University of Maryla
 nd - College Park\, 8228 Paint Branch Drive\, College Park\, Maryland\, Un
 ited States\, 20742
ORGANIZER:minwu@umd.edu
SEQUENCE:3
SUMMARY:SPS Lecture by Dr. Jie Liu on "Low-Energy and Flexible GPS Sensing 
 Through Cloud Offloading"
URL;VALUE=URI:https://events.vtools.ieee.org/m/44124
X-ALT-DESC:Description: <br /><p>This is sponsored by the University of Mar
 yland Booz Allen Hamilton Distinguished Colloquium Series of the Electrica
 l and Computer Engineering at University of Maryland\, College Park\, and 
 co-sponsored by the IEEE Signal Processing Washington Chapter.</p>\n<p>"Lo
 w-Energy and Flexible GPS Sensing Through Cloud Offloading"</p>\n<p>Speake
 r: Dr. Jie Liu (Microsoft Research -- Redmond\, WA)</p><br /><br />Agenda:
  <br /><p>3:15 - 3:30pm: &nbsp\;Checking in</p>\n<p>3:30 - 4:30pm: &nbsp\;
 Lecture by Dr. Jie Liu (Microsoft Research -- Redmond\, WA)</p>\n<p>4:30 -
  5:00pm: &nbsp\;Reception (with light refreshment)</p>\n<p><br />"Low-Ener
 gy and Flexible GPS Sensing Through Cloud Offloading"</p>\n<p>Location-bas
 ed services have become ubiquitous\, thanks to sensors like GPS and RF rec
 eivers in our smart phones. However\, the energy consumption of GPS receiv
 ing is a major bottleneck for long-term and frequent location sensing. In 
 this talk\, I will take a deep look into the GPS receiving pipeline and pr
 esent our efforts on a cloud-offloading approach to GPS-based location sen
 sing. The partitioning between device and cloud brings three kinds of bene
 fits. First\, we can reduce the device side energy consumption by orders o
 f magnitude. Second\, with the computation power in the cloud\, we can ach
 ieve high sensitivity and make GPS receiver work in many indoor places. Fi
 nally\, we can leverage opportunistic energy sources on the device side to
  reduce the amount of data to be transferred between device and cloud. The
  cloud-offloading architecture help push location sensing and tracking to 
 the next tier of IoT devices.</p>
END:VEVENT
END:VCALENDAR