110 citations · 183 across the 8 of their papers we have counts for
8 papers
Enhancing personalised thermal comfort models with Active Learning for improved HVAC controls
Zeynep Duygu Tekler, Yue Lei, Xilei Dai +1
Developing personalised thermal comfort models to inform occupant-centric controls (OCC) in buildings requires collecting large amounts of real-time occupant preference data. This…
BIM-to-BRICK: Using graph modeling for IoT/BMS and spatial semantic data interoperability within digital data models of buildings
Filippo Vittori, Chuan Fu Tan, Anna Laura Pisello +2
The holistic management of a building requires data from heterogeneous sources such as building management systems (BMS), Internet-of-Things (IoT) sensor networks, and building inf…
District-scale surface temperatures generated from high-resolution longitudinal thermal infrared images
Subin Lin, Vasantha Ramani, Miguel Martin +6
The paper describes a dataset that was collected by infrared thermography, which is a non-contact, non-intrusive technique to collect data and analyze the built environment in vari…
Machine Learning for Smart and Energy-Efficient Buildings
Hari Prasanna Das, Yu-Wen Lin, Utkarsha Agwan +7
Energy consumption in buildings, both residential and commercial, accounts for approximately 40% of all energy usage in the U.S., and similar numbers are being reported from countr…
Longitudinal thermal imaging for scalable non-residential HVAC and occupant behaviour characterization
Vasantha Ramani, Miguel Martin, Pandarasamy Arjunan +3
This work presents a study on the characterization of the air-conditioning (AC) usage pattern of non-residential buildings from thermal images collected from an urban-scale infrare…
Elastic buildings: Calibrated district-scale simulation of occupant-flexible campus operation for hybrid work optimization
Martín Mosteiro-Romero, Clayton Miller, Adrian Chong +1
Before 2020, the way occupants utilized the built environment had been changing slowly towards scenarios in which occupants have more choice and flexibility in where and how they w…
Personal thermal comfort models using digital twins: Preference prediction with BIM-extracted spatial-temporal proximity data from Build2Vec
Mahmoud Abdelrahman, Adrian Chong, Clayton Miller
Conventional thermal preference prediction in buildings has limitations due to the difficulty in capturing all environmental and personal factors. New model features can improve th…
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…