IoT for Low Carbon Design in Buildings
Abstract: It has been established that a 5 °C temperature increase 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 comes from heating or cooling systems. Since a person typically spends 90% of their time indoors, it is important to assure that these systems function adequately and that they provide 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 perception varies depending on the person’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 Adaptive method, that aims to find a range of temperature, rather than a fixed one. Hence, this presentation will present an initial proposal for a system for data collection and preprocessing, as well as its interpretation, visualization and derived actions for the benefit of the occupants, all with low cost sensors, aiming for this technology to be easily accessible to people from all socioeconomic backgrounds.
Date and Time
Location
Hosts
Registration
- Date: 07 Mar 2024
- Time: 01:15 PM UTC to 02:15 PM UTC
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- Ulster University Belfast Campus
- Belfast, Northern Ireland
- United Kingdom
- Building: BD-03-006
Speakers
Carlos Zepeda-Gil of University of Monterrey, Mexico
IoT for Low Carbon Design in Buildings
Abstract: It has been established that a 5 °C temperature increase 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 comes from heating or cooling systems. Since a person typically spends 90% of their time indoors, it is important to assure that these systems function adequately and that they provide 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 perception varies depending on the person’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 Adaptive method, that aims to find a range of temperature, rather than a fixed one. Hence, this presentation will present an initial proposal for a system for data collection and preprocessing, as well as its interpretation, visualization and derived actions for the benefit of the occupants, all with low cost sensors, aiming for this technology to be easily accessible to people from all socioeconomic backgrounds.
Biography:
Short Bio: Carlos Zepeda-Gil is an Associate Professor (Lecturer) at the University of Monterrey in Mexico. He is an Architect from the University of Liverpool and PhD in Architecture & Civil Engineering from the University of Bath. Carlos's research and teaching objectives focus on the design buildings that use the least amount of energy possible during their lifetime (from cradle to grave). A particular focus of Carlos's interest is on the health effects of the internal environments of homes inhabited by socially vulnerable sectors as well as their ability to provide healthy environments without increasing the building's carbon footprint. This touches on issues related to the thermodynamics of the building envelope, real-time thermal comfort feedback, and the role of sensors coupled with artificial intelligence algorithms.