An Occupant Centric Thermal Comfort System: Design and Implementation
Preliminaries of a study in which Personalised Comfort Nodes (PCN)—custom sensor modules that collect environmental & occupant thermal comfort data—are deployed to gather feedback from occupants of a commercial mixed-use building are presented. This data is used to inform Building Automation System (BAS) to maximise the occupant comfort. The main rationale of this research project is to assess the viability of scaling up occupant centric HVAC systems. We believe the main scalability constraint of such systems is not technological, but rather perceived cost of implementation and effectiveness in improving thermal comfort. The experimental design allows for comprehensive analyses of hardware and software development costs—in addition to system implementation, and on-going data management and system maintenance costs. Moreover, we believe there will be opportunities for granular assessment of occupant comfort. Reported occupant comfort data will be coupled with environmental parameters (e.g. temperature, humidity, CO2) to assess viability of finding common intervals for shared spaces. There will also be opportunities to optimise the occupant feedback collection methods & frequencies. This study may allow for a preliminary Benefit-Cost-Analysis (BCA) of increased occupant comfort, and corresponding costs of PCN system implementation & potential changes in energy demand.
Duzgun Agdas, PhD
Senior Lecturer of Construction Engineering and Management, Queensland University of Technology
Duzgun Agdas is a Senior Lecturer of Construction Engineering and Management within the School of Civil Engineering and Built Environment at the Science and Engineering Faculty of Queensland University of Technology (QUT). He completed his graduate studies at the University of Florida, where he worked post-graduation prior to starting his tenure-track job at QUT in 2014. His research interests include building energy efficiency, and infrastructure sustainability and disaster resilience. He is part of the Data Analytics in the Built Environment (DABE) research group, with fellow engineers and data scientist, which aims to find data driven solutions to grand challenges of built environment (https://research.qut.edu.au/dabe/). Further information about his research projects, publications and current supervision can be found on the following webpage: https://staff.qut.edu.au/staff/duzgun.agdas.