264 citations · 1.1k across the 18 of their papers we have counts for
6 papers · 1 filter
Balancing thermal comfort datasets: We GAN, but should we?
Matias Quintana, Stefano Schiavon, Kwok Wai Tham +1
Thermal comfort assessment for the built environment has become more available to analysts and researchers due to the proliferation of sensors and subjective feedback methods. Thes…
Humans-as-a-sensor for buildings: Intensive longitudinal indoor comfort models
Prageeth Jayathissa, Matias Quintana, Mahmoud Abdelrahman +1
Evaluating and optimising human comfort within the built environment is challenging due to the large number of physiological, psychological and environmental variables that affect…
The ASHRAE Great Energy Predictor III competition: Overview and results
Clayton Miller, Pandarasamy Arjunan, Anjukan Kathirgamanathan +8
In late 2019, ASHRAE hosted the Great Energy Predictor III (GEPIII) machine learning competition on the Kaggle platform. This launch marked the third energy prediction competition…
Build2Vec: Building Representation in Vector Space
Mahmoud Abdelrahman, Adrian Chong, Clayton Miller
In this paper, we represent a methodology of a graph embeddings algorithm that is used to transform labeled property graphs obtained from a Building Information Model (BIM). Indust…
Spacematch: Using environmental preferences to match occupants to suitable activity-based workspaces
Tapeesh Sood, Patrick Janssen, Clayton Miller
The activity-based workspace (ABW) paradigm is becoming more popular in commercial office spaces. In this strategy, occupants are given a choice of spaces to do their work and pers…
The Building Data Genome Project 2, energy meter data from the ASHRAE Great Energy Predictor III competition
Clayton Miller, Anjukan Kathirgamanathan, Bianca Picchetti +7
This paper describes an open data set of 3,053 energy meters from 1,636 non-residential buildings with a range of two full years (2016 and 2017) at an hourly frequency (17,544 meas…