Personal thermal comfort models using digital twins: Preference prediction with BIM-extracted spatial-temporal proximity data from Build2Vec

[1]  F. Biljecki,et al.  The Internet-of-Buildings (IoB) — Digital twin convergence of wearable and IoT data with GIS/BIM , 2021, Journal of Physics: Conference Series.

[2]  Giorgia Chinazzo,et al.  Investigating the indoor environmental quality of different workplaces through web-scraping and text-mining of Glassdoor reviews , 2021 .

[3]  Adrian Chong,et al.  Data science for building energy efficiency: A comprehensive text-mining driven review of scientific literature , 2021, Energy and Buildings.

[4]  S. Schiavon,et al.  Lessons learned from 20 years of CBE’s occupant surveys , 2021, Buildings and Cities.

[5]  A. Rysanek,et al.  Correlations between thermal satisfaction and non-thermal conditions of indoor environmental quality: Bayesian inference of a field study of offices , 2020 .

[6]  Francesco Goia,et al.  Field investigations of a smiley-face polling station for recording occupant satisfaction with indoor climate , 2020 .

[7]  Clayton Miller,et al.  Balancing thermal comfort datasets: We GAN, but should we? , 2020, BuildSys@SenSys.

[8]  Prageeth Jayathissa,et al.  Humans-as-a-sensor for buildings: Intensive longitudinal indoor comfort models , 2020, Buildings.

[9]  Clayton Miller,et al.  Build2Vec: Building Representation in Vector Space , 2020, ArXiv.

[10]  Zoltán Nagy,et al.  Introducing IEA EBC annex 79: Key challenges and opportunities in the field of occupant-centric building design and operation , 2020, Building and Environment.

[11]  Patrick Janssen,et al.  Spacematch: Using Environmental Preferences to Match Occupants to Suitable Activity-Based Workspaces , 2020, Frontiers in Built Environment.

[12]  Hui Zhang,et al.  The impact of a view from a window on thermal comfort, emotion, and cognitive performance , 2020, Building and Environment.

[13]  Jingsi Zhang,et al.  Comparing machine learning algorithms in predicting thermal sensation using ASHRAE Comfort Database II , 2020, Energy and Buildings.

[14]  Yury A. Malkov,et al.  Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Prageeth Jayathissa,et al.  The SDE4 Learning Trail: Crowdsourcing occupant comfort feedback at a net-zero energy building , 2019, Journal of Physics: Conference Series.

[16]  Prageeth Jayathissa,et al.  Is your clock-face cozie? A smartwatch methodology for the in-situ collection of occupant comfort data , 2019, Journal of Physics: Conference Series.

[17]  Jennifer A. Veitch,et al.  Bayesian inference of thermal comfort: evaluating the effect of “well-being” on perceived thermal comfort in open plan offices , 2019 .

[18]  Ming Jin,et al.  Personal thermal comfort models with wearable sensors , 2019, Building and Environment.

[19]  B. Becerik-Gerber,et al.  A comparative study of predicting individual thermal sensation and satisfaction using wrist-worn temperature sensor, thermal camera and ambient temperature sensor , 2019, Building and Environment.

[20]  Gail Brager,et al.  Analysis of the accuracy on PMV – PPD model using the ASHRAE Global Thermal Comfort Database II , 2019, Building and Environment.

[21]  Alex Parkinson,et al.  Continuous IEQ monitoring system: Context and development , 2019, Building and Environment.

[22]  Edward Arens,et al.  Occupant comfort and behavior: High-resolution data from a 6-month field study of personal comfort systems with 37 real office workers , 2019, Building and Environment.

[23]  Patrick X.W. Zou,et al.  Review of 10 years research on building energy performance gap: Life-cycle and stakeholder perspectives , 2018, Energy and Buildings.

[24]  Hyojin Kim,et al.  Development of the ASHRAE Global Thermal Comfort Database II , 2018, Building and Environment.

[25]  Richard de Dear,et al.  Individual difference in thermal comfort: A literature review , 2018, Building and Environment.

[26]  Gail Brager,et al.  Post-occupancy evaluation: State-of-the-art analysis and state-of-the-practice review , 2018 .

[27]  Joyce Kim,et al.  Personal comfort models – A new paradigm in thermal comfort for occupant-centric environmental control , 2018 .

[28]  Zoltán Nagy,et al.  Comprehensive analysis of the relationship between thermal comfort and building control research - A data-driven literature review , 2018 .

[29]  Carol C. Menassa,et al.  Personalized human comfort in indoor building environments under diverse conditioning modes , 2017 .

[30]  Norhayati Mahyuddin,et al.  A review on indoor environmental quality (IEQ) and energy consumption in building based on occupant behavior , 2017 .

[31]  Eva Krídlová Burdová,et al.  Indoor environmental quality of classrooms and occupants' comfort in a special education school in Slovak Republic , 2017 .

[32]  Ming Jin,et al.  Longitudinal Assessment of Thermal and Perceived Air Quality Acceptability in Relation to Temperature, Humidity, and CO2 Exposure in Singapore , 2017 .

[33]  Suzaini M. Zaid,et al.  Influence of Indoor Environmental Quality on Work Productivity in Green Office Buildings: a Review , 2017 .

[34]  Xiaofeng Li,et al.  Evaluation of perceived indoor environmental quality of five-star hotels in China: An application of online review analysis , 2017 .

[35]  Tat-Seng Chua,et al.  Learning from Collective Intelligence , 2016, ACM Trans. Multim. Comput. Commun. Appl..

[36]  Feiping Nie,et al.  Capped Lp-Norm Graph Embedding for Photo Clustering , 2016, ACM Multimedia.

[37]  Aditya Ponnada,et al.  μEMA: Microinteraction-based ecological momentary assessment (EMA) using a smartwatch , 2016, UbiComp.

[38]  Jure Leskovec,et al.  node2vec: Scalable Feature Learning for Networks , 2016, KDD.

[39]  Yacine Rezgui,et al.  Building energy metering and environmental monitoring – A state-of-the-art review and directions for future research , 2016 .

[40]  Charu C. Aggarwal,et al.  Heterogeneous Network Embedding via Deep Architectures , 2015, KDD.

[41]  Steven Skiena,et al.  DeepWalk: online learning of social representations , 2014, KDD.

[42]  Edward Arens,et al.  Indoor environmental quality assessment models: A literature review and a proposed weighting and classification scheme , 2013 .

[43]  Richard de Dear,et al.  Workspace satisfaction: The privacy-communication trade-off in open-plan offices - eScholarship , 2013 .

[44]  Jing Wang,et al.  Fast Neighborhood Graph Search Using Cartesian Concatenation , 2013, 2013 IEEE International Conference on Computer Vision.

[45]  Y Zhu,et al.  Progress in thermal comfort research over the last twenty years. , 2013, Indoor air.

[46]  Pascal Vincent,et al.  Representation Learning: A Review and New Perspectives , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[47]  Vivian Loftness,et al.  Investigation of human body skin temperatures as a bio-signal to indicate overall thermal sensations , 2012 .

[48]  Hui Zhang,et al.  Satisfaction and self-estimated performance in relation to indoor environmental parameters and building features , 2012 .

[49]  Richard de Dear,et al.  Nonlinear relationships between individual IEQ factors and overall workspace satisfaction , 2012 .

[50]  Jane Brennan,et al.  Spatial proximity is more than just a distance measure , 2012, Int. J. Hum. Comput. Stud..

[51]  Hui Zhang,et al.  Window performance for human thermal comfort , 2006 .