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DTSTAMP:20240315T123015Z
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DTSTART;TZID=Europe/London:20240307T131500
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DESCRIPTION:Abstract: It has been established that a 5 °C temperature incr
 ease due to climate change may be catastrophic in some areas of the world.
  Further\, Buildings are known to be responsible for 50% of the world’s 
 CO2 emissions\, where most of the energy that generates these emissions co
 mes from heating or cooling systems. Since a person typically spends 90% o
 f their time indoors\, it is important to assure that these systems functi
 on adequately and that they provide thermal comfort to at least 80% of the
  people within these buildings (and 90% in buildings with people with chro
 nical illnesses or the elderly). However\, fitting setpoints tend to be ar
 bitrary as the thermal perception varies depending on the person’s chara
 cteristics\, background\, gender\, etc. This means that buildings may be c
 onsuming more energy than necessary. The most accepted model to determine 
 Thermal Comfort is the Adaptive method\, that aims to find a range of temp
 erature\, rather than a fixed one. Hence\, this presentation will present 
 an initial proposal for a system for data collection and preprocessing\, a
 s well as its interpretation\, visualization and derived actions for the b
 enefit of the occupants\, all with low cost sensors\, aiming for this tech
 nology to be easily accessible to people from all socioeconomic background
 s.\n\nSpeaker(s): Carlos Zepeda-Gil\n\nBldg: BD-03-006\, Ulster University
  Belfast Campus\, Belfast\, Northern Ireland\, United Kingdom\, Virtual: h
 ttps://events.vtools.ieee.org/m/410044
LOCATION:Bldg: BD-03-006\, Ulster University Belfast Campus\, Belfast\, Nor
 thern Ireland\, United Kingdom\, Virtual: https://events.vtools.ieee.org/m
 /410044
ORGANIZER:m.garcia-constantino@ulster.ac.uk
SEQUENCE:2
SUMMARY:IoT for Low Carbon Design in Buildings
URL;VALUE=URI:https://events.vtools.ieee.org/m/410044
X-ALT-DESC:Description: <br /><p class="MsoNormal" style="text-align: justi
 fy\; text-autospace: none\;"><strong>Abstract: </strong>It has been establ
 ished that a 5 &deg\;C temperature increase due to climate change may be c
 atastrophic in some areas of the world. Further\, Buildings are known to b
 e responsible for 50% of the world&rsquo\;s CO2 emissions\, where most of 
 the energy that generates these emissions comes from heating or cooling sy
 stems. Since a person typically spends 90% of their time indoors\, it is i
 mportant to assure that these systems function adequately and that they pr
 ovide thermal comfort to at least 80% of the people within these buildings
  (and 90% in buildings with people with chronical illnesses or the elderly
 ). However\, fitting setpoints tend to be arbitrary as the thermal percept
 ion varies depending on the person&rsquo\;s characteristics\, background\,
  gender\, etc. This means that buildings may be consuming more energy than
  necessary. The most accepted model to determine Thermal Comfort is the Ad
 aptive method\, that aims to find a range of temperature\, rather than a f
 ixed one. Hence\, this presentation will present an initial proposal for a
  system for data collection and preprocessing\, as well as its interpretat
 ion\, visualization and derived actions for the benefit of the occupants\,
  all with low cost sensors\, aiming for this technology to be easily acces
 sible to people from all socioeconomic backgrounds.</p>
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