• Upasani N, Guerra-Santin O and Mohammadi M. (2024). Developing Building-Specific, Occupant-Centric Thermal Comfort Models: A Methodological Approach. Journal of Building Engineering. 10.1016/j.jobe.2024.110281. (110281). Online publication date: 1-Jul-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S2352710224018497

  • Soleimanijavid A, Konstantzos I and Liu X. (2024). Challenges and opportunities of occupant-centric building controls in real-world implementation: A critical review. Energy and Buildings. 10.1016/j.enbuild.2024.113958. (113958). Online publication date: 1-Feb-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S0378778824000744

  • Yano T and Sako M. Energy-Saving Occupant-Feedback Control Method Under Preferred Air-Conditioner Settings of Occupants. IEEE Access. 10.1109/ACCESS.2024.3367954. 12. (29126-29143).

    https://ieeexplore.ieee.org/document/10440346/

  • Skaloumpakas P, Sarmas E, Mylona Z, Cavadenti A, Santori F and Marinakis V. (2023). Predicting Thermal Comfort in Buildings With Machine Learning and Occupant Feedback 2023 IEEE International Workshop on Metrology for Living Environment (MetroLivEnv). 10.1109/MetroLivEnv56897.2023.10164051. 978-1-6654-5693-7. (34-39).

    https://ieeexplore.ieee.org/document/10164051/

  • Emad-Ud-Din M and Wang Y. (2023). Indoor Occupancy Sensing via Networked Nodes (2012–2022): A Review. Future Internet. 10.3390/fi15030116. 15:3. (116).

    https://www.mdpi.com/1999-5903/15/3/116

  • Rosenberger J, Guo Z, Coffman A, Agdas D and Barooah P. (2022). An Open-Source Platform for Indoor Environment Monitoring with Participatory Comfort Sensing. Sensors. 10.3390/s23010364. 23:1. (364).

    https://www.mdpi.com/1424-8220/23/1/364

  • Rehman S, Javed A, Khan M, Nazar Awan M, Farukh A and Hussien A. (2020). PersonalisedComfort: a personalised thermal comfort model to predict thermal sensation votes for smart building residents. Enterprise Information Systems. 10.1080/17517575.2020.1852316. 16:7. Online publication date: 3-Jul-2022.

    https://www.tandfonline.com/doi/full/10.1080/17517575.2020.1852316

  • Zheng Z, Luo P, Li Y, Luo S, Jian J and Huang Z. Towards lifelong thermal comfort prediction with KubeEdge-sedna. Proceedings of the Thirteenth ACM International Conference on Future Energy Systems. (263-276).

    https://doi.org/10.1145/3538637.3538856

  • Rajabi H, Hu Z, Ding X, Pan S, Du W and Cerpa A. MODES. Proceedings of the Thirteenth ACM International Conference on Future Energy Systems. (228-239).

    https://doi.org/10.1145/3538637.3538852

  • Ramallo-González A, Bardaki C, Kotsopoulos D, Tomat V, González Vidal A, Fernandez Ruiz P and Skarmeta Gómez A. (2022). Reducing Energy Consumption in the Workplace via IoT-Allowed Behavioural Change Interventions. Buildings. 10.3390/buildings12060708. 12:6. (708).

    https://www.mdpi.com/2075-5309/12/6/708

  • Sheikh Khan D and Kolarik J. (2021). Can occupant voting systems provide energy savings and improved occupant satisfaction in buildings?—a review. Science and Technology for the Built Environment. 10.1080/23744731.2021.1976017. 28:2. (221-239). Online publication date: 7-Feb-2022.

    https://www.tandfonline.com/doi/full/10.1080/23744731.2021.1976017

  • Pandharipande A, Lankhorst M and Frimout E. Luminaire-Based Multi-Modal Sensing for Environmental Building Applications. IEEE Sensors Journal. 10.1109/JSEN.2021.3137542. 22:3. (2564-2571).

    https://ieeexplore.ieee.org/document/9658523/

  • Yoon Y, Lee Y, Kim S, Kim J and Moon H. (2022). A non-intrusive data-driven model for detailed occupants’ activities classification in residential buildings using environmental and energy usage data. Energy and Buildings. 10.1016/j.enbuild.2021.111699. 256. (111699). Online publication date: 1-Feb-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S037877882100983X

  • Sheikh Khan D, Kolarik J and Weitzmann P. (2021). Application of an occupant voting system for continuous occupant feedback on thermal and indoor air quality – Case studies in office spaces. Energy and Buildings. 10.1016/j.enbuild.2021.111363. 251. (111363). Online publication date: 1-Nov-2021.

    https://linkinghub.elsevier.com/retrieve/pii/S0378778821006472

  • Zhang H and Tzempelikos A. (2021). Thermal preference-based control studies: review and detailed classification. Science and Technology for the Built Environment. 10.1080/23744731.2021.1877041. 27:8. (1031-1039). Online publication date: 14-Sep-2021.

    https://www.tandfonline.com/doi/full/10.1080/23744731.2021.1877041

  • Liu X, Lee S, Bilionis I, Karava P, Joe J and Sadeghi S. (2021). A user-interactive system for smart thermal environment control in office buildings. Applied Energy. 10.1016/j.apenergy.2021.117005. 298. (117005). Online publication date: 1-Sep-2021.

    https://linkinghub.elsevier.com/retrieve/pii/S0306261921004736

  • Lassen N, Hegli T, Dokka T, Løvold T, Edwards K, Goia F and Andresen I. (2021). Enabling holistic design for high energy efficient office buildings through the use of subjective occupant feedback. Sustainable Cities and Society. 10.1016/j.scs.2021.102867. 69. (102867). Online publication date: 1-Jun-2021.

    https://linkinghub.elsevier.com/retrieve/pii/S2210670721001578

  • Lassen N and Goia F. (2021). A theoretical framework for classifying occupant-centric data streams on indoor climate using a physiological and cognitive process hierarchy. Energy and Buildings. 10.1016/j.enbuild.2021.110935. 241. (110935). Online publication date: 1-Jun-2021.

    https://linkinghub.elsevier.com/retrieve/pii/S037877882100219X

  • Zhou Y, Su Y, Xu Z, Wang X, Wu J and Guan X. (2021). A hybrid physics-based/data-driven model for personalized dynamic thermal comfort in ordinary office environment. Energy and Buildings. 10.1016/j.enbuild.2021.110790. 238. (110790). Online publication date: 1-May-2021.

    https://linkinghub.elsevier.com/retrieve/pii/S0378778821000748

  • Nagarathinam S, Vasan A, Sarangan V, Jayaprakash R and Sivasubramaniam A. (2021). User Placement and Optimal Cooling Energy for Co-working Building Spaces. ACM Transactions on Cyber-Physical Systems. 5:2. (1-24). Online publication date: 30-Apr-2021.

    https://doi.org/10.1145/3432818

  • Sheikh Khan D, Kolarik J and Weitzmann P. (2021). Occupants’ Interaction With an Occupant Voting System for Thermal and Indoor Air Quality Feedback – Case Studies in Office Spaces. Frontiers in Built Environment. 10.3389/fbuil.2021.643630. 7.

    https://www.frontiersin.org/articles/10.3389/fbuil.2021.643630/full

  • Li Q, Han J and Lu L. (2021). A Random Forest Classification Algorithm Based Personal Thermal Sensation Model for Personalized Conditioning System in Office Buildings. The Computer Journal. 10.1093/comjnl/bxaa165.

    https://academic.oup.com/comjnl/advance-article/doi/10.1093/comjnl/bxaa165/6120296

  • Sarker A, Yao F, Shen H, Zhao H, Zhu H, Lone H, Barnes L, Campbell B and Rosen M. (2020). Deep Learning Based Prediction Towards Designing A Smart Building Assistant System 2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS). 10.1109/MASS50613.2020.00034. 978-1-7281-9866-8. (202-210).

    https://ieeexplore.ieee.org/document/9356025/

  • Trivedi D and Badarla V. (2019). Occupancy detection systems for indoor environments: A survey of approaches and methods. Indoor and Built Environment. 10.1177/1420326X19875621. 29:8. (1053-1069). Online publication date: 1-Oct-2020.

    https://journals.sagepub.com/doi/10.1177/1420326X19875621

  • Lee S and Karava P. (2020). Towards smart buildings with self-tuned indoor thermal environments – A critical review. Energy and Buildings. 10.1016/j.enbuild.2020.110172. 224. (110172). Online publication date: 1-Oct-2020.

    https://linkinghub.elsevier.com/retrieve/pii/S0378778819338885

  • Tomat V, Ramallo-González A and Skarmeta Gómez A. (2020). A Comprehensive Survey about Thermal Comfort under the IoT Paradigm: Is Crowdsensing the New Horizon?. Sensors. 10.3390/s20164647. 20:16. (4647).

    https://www.mdpi.com/1424-8220/20/16/4647

  • Ramallo-González A, Tomat V, Fernández-Ruiz P, Zamora-Izquierdo M and Skarmeta-Gómez A. (2020). Conceptualisation of an IoT Framework for Multi-Person Interaction with Conditioning Systems. Energies. 10.3390/en13123094. 13:12. (3094).

    https://www.mdpi.com/1996-1073/13/12/3094

  • Jung W and Jazizadeh F. (2020). Energy saving potentials of integrating personal thermal comfort models for control of building systems: Comprehensive quantification through combinatorial consideration of influential parameters. Applied Energy. 10.1016/j.apenergy.2020.114882. 268. (114882). Online publication date: 1-Jun-2020.

    https://linkinghub.elsevier.com/retrieve/pii/S0306261920303949

  • Winkler D, Yadav A, Chitu C and Cerpa A. (2020). OFFICE: Optimization Framework For Improved Comfort & Efficiency 2020 19th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). 10.1109/IPSN48710.2020.00030. 978-1-7281-5497-8. (265-276).

    https://ieeexplore.ieee.org/document/9110978/

  • Konis K, Blessenohl S, Kedia N and Rahane V. (2020). TrojanSense, a participatory sensing framework for occupant-aware management of thermal comfort in campus buildings. Building and Environment. 10.1016/j.buildenv.2019.106588. 169. (106588). Online publication date: 1-Feb-2020.

    https://linkinghub.elsevier.com/retrieve/pii/S0360132319308005

  • Yano T. Space Heating Control by Estimating Acceptable Set-Point Temperature Based on Survival Analysis. IEEE Access. 10.1109/ACCESS.2020.2967057. 8. (17956-17964).

    https://ieeexplore.ieee.org/document/8962075/

  • Feng Y, Wang N and Wang J. (2020). Design of Real-Time Individualized Comfort Monitor System Used in Healthcare Facilities. HCI International 2020 – Late Breaking Papers: Digital Human Modeling and Ergonomics, Mobility and Intelligent Environments. 10.1007/978-3-030-59987-4_19. (261-270).

    http://link.springer.com/10.1007/978-3-030-59987-4_19

  • Lee S, Karava P, Tzempelikos A and Bilionis I. (2019). Integrating occupants’ voluntary thermal preference responses into personalized thermal control in office buildings. Journal of Physics: Conference Series. 10.1088/1742-6596/1343/1/012138. 1343. (012138). Online publication date: 1-Nov-2019.

    https://iopscience.iop.org/article/10.1088/1742-6596/1343/1/012138

  • Chitu C, Stamatescu G and Cerpa A. (2019). Building Occupancy Estimation using Supervised Learning Techniques 2019 23rd International Conference on System Theory, Control and Computing (ICSTCC). 10.1109/ICSTCC.2019.8885985. 978-1-7281-0699-1. (167-172).

    https://ieeexplore.ieee.org/document/8885985/

  • Tariq Z, Imam M, Kar K and Mishra S. Experimental Evaluation of Data-Driven Predictive Indoor Thermal Management. Proceedings of the Tenth ACM International Conference on Future Energy Systems. (531-535).

    https://doi.org/10.1145/3307772.3331031

  • Aryal A, Becerik-Gerber B, Anselmo F, Roll S and Lucas G. (2019). Smart Desks to Promote Comfort, Health, and Productivity in Offices: A Vision for Future Workplaces. Frontiers in Built Environment. 10.3389/fbuil.2019.00076. 5.

    https://www.frontiersin.org/article/10.3389/fbuil.2019.00076/full

  • Alonso L. (2019). The Use of Citizen Science in the Characterization of the Lyon's Urban Heat and Cool Islands 2019 20th IEEE International Conference on Mobile Data Management (MDM). 10.1109/MDM.2019.00-18. 978-1-7281-3363-8. (387-388).

    https://ieeexplore.ieee.org/document/8788767/

  • Song M, Mao N, Xu Y and Deng S. (2019). Challenges in, and the development of, building energy saving techniques, illustrated with the example of an air source heat pump. Thermal Science and Engineering Progress. 10.1016/j.tsep.2019.03.002. 10. (337-356). Online publication date: 1-May-2019.

    https://linkinghub.elsevier.com/retrieve/pii/S2451904918306140

  • Tsolakis A, Moschos I, Zerzelidis A, Tropios P, Zikos S, Tryferidis A, Krinidis S, Ioannidis D and Tzovaras D. (2019). Occupancy-based decision support system for building management: From automation to end-user persuasion. International Journal of Energy Research. 10.1002/er.4445.

    http://doi.wiley.com/10.1002/er.4445

  • Rashid S, Haider Z, Chapal Hossain S, Memon K, Panhwar F, Mbogba M, Hu P and Zhao G. (2019). Retrofitting low-cost heating ventilation and air-conditioning systems for energy management in buildings. Applied Energy. 10.1016/j.apenergy.2018.12.020. 236. (648-661). Online publication date: 1-Feb-2019.

    https://linkinghub.elsevier.com/retrieve/pii/S0306261918318397

  • Yano T, Sako M, Tanabe S, Zhang H, Kurnitski J, Gameiro da Silva M, Nastase I, Wargocki P, Cao G, Mazzarela L and Inard C. (2019). A field study of space heating control using acceptable set-point temperature estimation: winter experiment in Japan office. E3S Web of Conferences. 10.1051/e3sconf/201911105001. 111. (05001).

    https://www.e3s-conferences.org/10.1051/e3sconf/201911105001

  • Gupta S, Kar K, Mishra S and Wen J. Incentive-Based Mechanism for Truthful Occupant Comfort Feedback in Human-in-the-Loop Building Thermal Management. IEEE Systems Journal. 10.1109/JSYST.2017.2771528. 12:4. (3725-3736).

    https://ieeexplore.ieee.org/document/8115164/

  • Abbas S, Bakar A, Chandio Y, Hafeez K, Ali A, Jadoon T and Alizai M. (2018). Inverted HVAC. ACM Transactions on Sensor Networks. 14:3-4. (1-26). Online publication date: 30-Nov-2018.

    https://doi.org/10.1145/3229063

  • Kim Y. Optimal Price Based Demand Response of HVAC Systems in Multizone Office Buildings Considering Thermal Preferences of Individual Occupants Buildings. IEEE Transactions on Industrial Informatics. 10.1109/TII.2018.2790429. 14:11. (5060-5073).

    https://ieeexplore.ieee.org/document/8248801/

  • Aryal A, Anselmo F and Becerik-Gerber B. Smart IoT desk for personalizing indoor environmental conditions. Proceedings of the 8th International Conference on the Internet of Things. (1-6).

    https://doi.org/10.1145/3277593.3277614

  • Yano T. (2018). Switch On/Interruption Control of Cooling Based on Estimated Acceptable Interruption Duration: An Office Case Study in Japan IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society. 10.1109/IECON.2018.8591659. 978-1-5090-6684-1. (826-831).

    https://ieeexplore.ieee.org/document/8591659/

  • Wang T, Xu Y, Withanage C, Lan L, Ahipasaoglu S and Courcoubetis C. A Fair and Budget-Balanced Incentive Mechanism for Energy Management in Buildings. IEEE Transactions on Smart Grid. 10.1109/TSG.2016.2628165. 9:4. (3143-3153).

    https://ieeexplore.ieee.org/document/7742350/

  • Siy C and Pedrasa J. (2018). A Fair Aggregation Scheme in Shared Space Settings 2018 IEEE Region Ten Symposium (Tensymp). 10.1109/TENCONSpring.2018.8691961. 978-1-5386-6989-1. (149-154).

    https://ieeexplore.ieee.org/document/8691961/

  • Yang L, Zheng Z, Sun J, Wang D and Li X. A Domain-Assisted Data Driven Model for Thermal Comfort Prediction in Buildings. Proceedings of the Ninth International Conference on Future Energy Systems. (271-276).

    https://doi.org/10.1145/3208903.3208914

  • Tariq Z, Kar K, Mishra S and Wen J. (2018). Enabling Better Thermal Management of Indoor Spaces through Adaptive Zonal Heat Transfer 2018 Annual American Control Conference (ACC). 10.23919/ACC.2018.8430838. 978-1-5386-5428-6. (5418-5423).

    https://ieeexplore.ieee.org/document/8430838/

  • Pazhoohesh M and Zhang C. (2018). Investigating Occupancy-Driven Air-Conditioning Control Based on Thermal Comfort Level. Journal of Architectural Engineering. 10.1061/(ASCE)AE.1943-5568.0000295. 24:2. Online publication date: 1-Jun-2018.

    https://ascelibrary.org/doi/10.1061/%28ASCE%29AE.1943-5568.0000295

  • Zhang Y, Li B and Hong J. (2017). Using Online Geotagged and Crowdsourced Data to Understand Human Offline Behavior in the City. ACM Transactions on Intelligent Systems and Technology. 9:3. (1-24). Online publication date: 31-May-2018.

    https://doi.org/10.1145/3078851

  • Wang P, Liu G, Fu Y, Zhou Y and Li J. (2017). Spotting Trip Purposes from Taxi Trajectories. ACM Transactions on Intelligent Systems and Technology. 9:3. (1-26). Online publication date: 31-May-2018.

    https://doi.org/10.1145/3078849

  • Liu J, Liu B, Liu Y, Chen H, Feng L, Xiong H and Huang Y. (2017). Personalized Air Travel Prediction. ACM Transactions on Intelligent Systems and Technology. 9:3. (1-26). Online publication date: 31-May-2018.

    https://doi.org/10.1145/3078845

  • Auffenberg F, Snow S, Stein S and Rogers A. (2017). A Comfort-Based Approach to Smart Heating and Air Conditioning. ACM Transactions on Intelligent Systems and Technology. 9:3. (1-20). Online publication date: 31-May-2018.

    https://doi.org/10.1145/3057730

  • Nacci A, Rana V, Balaji B, Spoletini P, Gupta R, Sciuto D and Agarwal Y. (2018). BuildingRules. ACM Transactions on Cyber-Physical Systems. 2:2. (1-22). Online publication date: 30-Apr-2018.

    https://doi.org/10.1145/3185500

  • Clear A, Mitchell Finnigan S, Olivier P and Comber R. ThermoKiosk. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. (1-12).

    https://doi.org/10.1145/3173574.3173956

  • Demertzis I, Papadopoulos S, Papapetrou O, Deligiannakis A, Garofalakis M and Papamanthou C. (2018). Practical Private Range Search in Depth. ACM Transactions on Database Systems. 43:1. (1-52). Online publication date: 31-Mar-2018.

    https://doi.org/10.1145/3167971

  • Noorwali I. (2018). Stakeholder Concern-Driven Requirements Analytics. ACM SIGSOFT Software Engineering Notes. 43:1. (1-6). Online publication date: 28-Mar-2018.

    https://doi.org/10.1145/3178315.3178324

  • Simo-Serra E, Iizuka S and Ishikawa H. (2018). Mastering Sketching. ACM Transactions on Graphics. 37:1. (1-13). Online publication date: 28-Feb-2018.

    https://doi.org/10.1145/3132703

  • Yano T. (2018). Space heating control using acceptable set-point temperature estimation by a statistical approach in the lyon smart community project 2018 IEEE International Conference on Industrial Technology (ICIT). 10.1109/ICIT.2018.8352428. 978-1-5090-5949-2. (1645-1650).

    https://ieeexplore.ieee.org/document/8352428/

  • Wang N, Phelan P, Harris C, Langevin J, Nelson B and Sawyer K. (2018). Past visions, current trends, and future context: A review of building energy, carbon, and sustainability. Renewable and Sustainable Energy Reviews. 10.1016/j.rser.2017.04.114. 82. (976-993). Online publication date: 1-Feb-2018.

    https://linkinghub.elsevier.com/retrieve/pii/S1364032117306159

  • Jung W and Jazizadeh F. (2018). Multi-occupancy Indoor Thermal Condition Optimization in Consideration of Thermal Sensitivity. Advanced Computing Strategies for Engineering. 10.1007/978-3-319-91638-5_12. (232-242).

    http://link.springer.com/10.1007/978-3-319-91638-5_12

  • Abedi M, Jazizadeh F, Huang B and Battaglia F. (2018). Smart HVAC Systems — Adjustable Airflow Direction. Advanced Computing Strategies for Engineering. 10.1007/978-3-319-91638-5_10. (193-209).

    http://link.springer.com/10.1007/978-3-319-91638-5_10

  • Wen J and Mishra S. (2018). Introduction and Overview. Intelligent Building Control Systems. 10.1007/978-3-319-68462-8_1. (1-8).

    http://link.springer.com/10.1007/978-3-319-68462-8_1

  • Gupta S, Kar K, Mishra S and Wen J. (2017). Singular Perturbation Method for Smart Building Temperature Control Using Occupant Feedback. Asian Journal of Control. 10.1002/asjc.1587. 20:1. (386-402). Online publication date: 1-Jan-2018.

    https://onlinelibrary.wiley.com/doi/10.1002/asjc.1587

  • Huberman B. (2017). Big Data and the Attention Economy. Ubiquity. 2017:December. (1-7). Online publication date: 12-Dec-2017.

    https://doi.org/10.1145/3158337

  • Thomas A, Menassa C and Kamat V. (2017). Lightweight and adaptive building simulation (LABS) framework for integrated building energy and thermal comfort analysis. Building Simulation. 10.1007/s12273-017-0409-5. 10:6. (1023-1044). Online publication date: 1-Dec-2017.

    http://link.springer.com/10.1007/s12273-017-0409-5

  • Shin E, Yus R, Mehrotra S and Venkatasubramanian N. Exploring fairness in participatory thermal comfort control in smart buildings. Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments. (1-10).

    https://doi.org/10.1145/3137133.3137156

  • Hafeez K, Chandio Y, Bakar A, Ali A, Syed A, Jadoon T and Alizai M. Inverting HVAC for energy efficient thermal comfort in populous emerging countries. Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments. (1-10).

    https://doi.org/10.1145/3137133.3137137

  • Xiao J, Xie J, Chen X, Yu K, Chen Z and Li Z. (2017). Energy cost reduction robust optimization for meeting scheduling in smart commercial buildings 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2). 10.1109/EI2.2017.8245295. 978-1-5386-1427-3. (1-5).

    http://ieeexplore.ieee.org/document/8245295/

  • Li D, Menassa C and Kamat V. (2017). A Personalized HVAC Control Smartphone Application Framework for Improved Human Health and Well-Being ASCE International Workshop on Computing in Civil Engineering 2017. 10.1061/9780784480830.011. 9780784480830. (82-90). Online publication date: 22-Jun-2017.

    http://ascelibrary.org/doi/10.1061/9780784480830.011

  • Alshehri F, Kenny P and O'Donnell J. Requirements for BIM-based thermal comfort analysis. Proceedings of the Symposium on Simulation for Architecture and Urban Design. (1-8).

    /doi/10.5555/3289787.3289789

  • Snow S, Auffenberg F and schraefel m. Log it While it's Hot. Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. (1595-1606).

    https://doi.org/10.1145/3025453.3025578

  • Guo X, Zheng X and He Y. (2017). WiZig: Cross-technology energy communication over a noisy channel IEEE INFOCOM 2017 - IEEE Conference on Computer Communications. 10.1109/INFOCOM.2017.8057108. 978-1-5090-5336-0. (1-9).

    http://ieeexplore.ieee.org/document/8057108/

  • Guo F, Zhou B and Vuran M. (2017). CFOSynt: Carrier frequency offset assisted clock syntonization for wireless sensor networks IEEE INFOCOM 2017 - IEEE Conference on Computer Communications. 10.1109/INFOCOM.2017.8057075. 978-1-5090-5336-0. (1-9).

    http://ieeexplore.ieee.org/document/8057075/

  • Barrios L and Kleiminger W. (2017). The Comfstat - automatically sensing thermal comfort for smart thermostats 2017 IEEE International Conference on Pervasive Computing and Communications (PerCom). 10.1109/PERCOM.2017.7917872. 978-1-5090-4327-9. (257-266).

    http://ieeexplore.ieee.org/document/7917872/

  • Clear A, Finnigan S, Olivier P and Comber R. "I'd Want to Burn the Data or at Least Nobble the Numbers". Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing. (2448-2461).

    https://doi.org/10.1145/2998181.2998188

  • Stamatescu G, Beltran A and Cerpa A. Data-driven Comfort Models for User-centric Predictive Control in Smart Buildings. Proceedings of the 3rd ACM International Conference on Systems for Energy-Efficient Built Environments. (221-222).

    https://doi.org/10.1145/2993422.2996394

  • Siy C and Pedrasa J. (2016). Space comfort maximization - a review TENCON 2016 - 2016 IEEE Region 10 Conference. 10.1109/TENCON.2016.7848460. 978-1-5090-2597-8. (2396-2400).

    http://ieeexplore.ieee.org/document/7848460/

  • Chinh H, Shetty S, Gupta M and Panda S. (2016). A wireless sensor and actuator network (WSAN) framework for personalized thermal comfort in office buildings 2016 IEEE International Conference on Sustainable Energy Technologies (ICSET). 10.1109/ICSET.2016.7811754. 978-1-5090-5200-4. (42-47).

    http://ieeexplore.ieee.org/document/7811754/

  • Shetty S, Hoang Duc Chinh , Gupta M and Panda S. (2016). Personal thermal comfort management in existing office buildings using energy-efficient fans IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society. 10.1109/IECON.2016.7793711. 978-1-5090-3474-1. (7083-7088).

    http://ieeexplore.ieee.org/document/7793711/

  • Mirakhorli A and Dong B. (2016). Occupancy behavior based model predictive control for building indoor climate—A critical review. Energy and Buildings. 10.1016/j.enbuild.2016.07.036. 129. (499-513). Online publication date: 1-Oct-2016.

    https://linkinghub.elsevier.com/retrieve/pii/S0378778816306338

  • Balaji B, Koh J, Weibel N and Agarwal Y. Genie. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. (1200-1211).

    https://doi.org/10.1145/2971648.2971719

  • Winkler D, Beltran A, Esfahani N, Maglio P and Cerpa A. FORCES. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. (1188-1199).

    https://doi.org/10.1145/2971648.2971700

  • Ranjan J and Scott J. ThermalSense. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. (1212-1222).

    https://doi.org/10.1145/2971648.2971659

  • Zhang D, Li S, Sun M and O'Neill Z. An Optimal and Learning-Based Demand Response and Home Energy Management System. IEEE Transactions on Smart Grid. 10.1109/TSG.2016.2552169. 7:4. (1790-1801).

    http://ieeexplore.ieee.org/document/7450180/

  • Stamatescu G and Stamatescu I. (2016). Open and closed loop simulation for predictive control of buildings 2016 24th Mediterranean Conference on Control and Automation (MED). 10.1109/MED.2016.7536017. 978-1-4673-8345-5. (304-309).

    http://ieeexplore.ieee.org/document/7536017/

  • Furst J, Chen K, Katz R and Bonnet P. (2016). Crowd-sourced BMS point matching and metadata maintenance with Babel 2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops). 10.1109/PERCOMW.2016.7457102. 978-1-5090-1941-0. (1-6).

    http://ieeexplore.ieee.org/document/7457102/

  • Sarkar C, S.N. A and Prasad V. iLTC: Achieving Individual Comfort in Shared Spaces. Proceedings of the 2016 International Conference on Embedded Wireless Systems and Networks. (65-76).

    /doi/10.5555/2893711.2893723

  • Zhou Y, Li D and Spanos C. Learning Optimization Friendly Comfort Model for HVAC Model Predictive Control. Proceedings of the 2015 IEEE International Conference on Data Mining Workshop (ICDMW). (430-439).

    https://doi.org/10.1109/ICDMW.2015.119

  • Fürst J, Chen K, Katz R and Bonnet P. Demo Abstract. Proceedings of the 2nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments. (101-102).

    https://doi.org/10.1145/2821650.2830303

  • Gupta S, Kar K, Mishra S and Wen J. Collaborative Energy and Thermal Comfort Management Through Distributed Consensus Algorithms. IEEE Transactions on Automation Science and Engineering. 10.1109/TASE.2015.2468730. 12:4. (1285-1296).

    http://ieeexplore.ieee.org/document/7236934/

  • Karmakar G, Kabra A and Ramamritham K. (2015). Maintaining thermal comfort in buildings. Real-Time Systems. 51:5. (485-525). Online publication date: 1-Sep-2015.

    https://doi.org/10.1007/s11241-015-9231-2

  • Shetty S, Chinh H and Panda S. (2015). Strategies for thermal comfort improvement and energy savings in existing office buildings using occupant feedback 2015 IEEE International Conference on Building Efficiency and Sustainable Technologies (ICBEST). 10.1109/ICBEST.2015.7435859. 978-1-5090-0160-6. (23-27).

    http://ieeexplore.ieee.org/document/7435859/

  • Farhan A, Pattipati K, Wang B and Luh P. (2015). Predicting individual thermal comfort using machine learning algorithms 2015 IEEE International Conference on Automation Science and Engineering (CASE). 10.1109/CoASE.2015.7294164. 978-1-4673-8183-3. (708-713).

    http://ieeexplore.ieee.org/document/7294164/

  • Gupta S, Kar K, Mishra S and Wen J. (2015). Incentive compatible mechanism for coordinated temperature control in multi-occupant buildings 2015 IEEE International Conference on Automation Science and Engineering (CASE). 10.1109/CoASE.2015.7294118. 978-1-4673-8183-3. (438-443).

    http://ieeexplore.ieee.org/document/7294118/

  • Auffenberg F, Stein S and Rogers A. A personalised thermal comfort model using a Bayesian network. Proceedings of the 24th International Conference on Artificial Intelligence. (2547-2553).

    /doi/10.5555/2832581.2832605

  • Gupta S, Kar K, Mishra S and Wen J. (2015). Distributed consensus algorithms for collaborative temperature control in smart buildings 2015 American Control Conference (ACC). 10.1109/ACC.2015.7172241. 978-1-4799-8684-2. (5758-5763).

    http://ieeexplore.ieee.org/document/7172241/

  • Yin S, Li Q and Gnawali O. Interconnecting WiFi Devices with IEEE 802.15.4 Devices without Using a Gateway. Proceedings of the 2015 International Conference on Distributed Computing in Sensor Systems. (127-136).

    https://doi.org/10.1109/DCOSS.2015.42

  • Majethia R, Mishra V, Pathak P, Lohani D, Acharya D and Sehrawat S. (2015). Contextual sensitivity of the ambient temperature sensor in Smartphones 2015 7th International Conference on Communication Systems and Networks (COMSNETS). 10.1109/COMSNETS.2015.7098674. 978-1-4799-8439-8. (1-8).

    http://ieeexplore.ieee.org/document/7098674/

  • Zhang L, Lam A and Wang D. Strategy-proof thermal comfort voting in buildings. Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings. (160-163).

    https://doi.org/10.1145/2674061.2674074

  • Li C, Li Z, Li M, Meggers F, Schlueter A and Lim H. Energy Efficient HVAC System with Distributed Sensing and Control. Proceedings of the 2014 IEEE 34th International Conference on Distributed Computing Systems. (429-438).

    https://doi.org/10.1109/ICDCS.2014.51

  • Lam A, Yuan Y and Wang D. An occupant-participatory approach for thermal comfort enhancement and energy conservation in buildings. Proceedings of the 5th international conference on Future energy systems. (133-143).

    https://doi.org/10.1145/2602044.2602067

  • Klingensmith N, Bomber J and Banerjee S. Hot, cold and in between. Proceedings of the 5th international conference on Future energy systems. (123-132).

    https://doi.org/10.1145/2602044.2602049

  • Kazmi A, O'grady M, Delaney D, Ruzzelli A and O'hare G. (2014). A Review of Wireless-Sensor-Network-Enabled Building Energy Management Systems. ACM Transactions on Sensor Networks. 10:4. (1-43). Online publication date: 1-Jun-2014.

    https://doi.org/10.1145/2532644

  • Kusy B, Rana R, Valencia P, Jurdak R and Wall J. (2014). Experiences with Sensors for Energy Efficiency in Commercial Buildings. Real-World Wireless Sensor Networks. 10.1007/978-3-319-03071-5_23. (231-243).

    https://link.springer.com/10.1007/978-3-319-03071-5_23

  • Pan D, Wang D, Cao J, Peng Y and Peng X. Minimizing Building Electricity Costs in a Dynamic Power Market. Proceedings of the 2013 IEEE 34th Real-Time Systems Symposium. (107-117).

    https://doi.org/10.1109/RTSS.2013.19

  • Balaji B, Teraoka H, Gupta R and Agarwal Y. ZonePAC. Proceedings of the 5th ACM Workshop on Embedded Systems For Energy-Efficient Buildings. (1-8).

    https://doi.org/10.1145/2528282.2528304

  • Hang-yat L and Wang D. Carrying My Environment with Me. Proceedings of the 5th ACM Workshop on Embedded Systems For Energy-Efficient Buildings. (1-8).

    https://doi.org/10.1145/2528282.2528286

  • Yuan Y, Pan D, Wang D, Xu X, Peng Y, Peng X and Wan P. (2013). A study towards applying thermal inertia for energy conservation in rooms. ACM Transactions on Sensor Networks. 10:1. (1-25). Online publication date: 1-Nov-2013.

    https://doi.org/10.1145/2529050

  • Purdon S, Kusy B, Jurdak R and Challen G. (2013). Model-free HVAC control using occupant feedback 2013 IEEE 38th Conference on Local Computer Networks Workshops (LCN Workshops). 10.1109/LCNW.2013.6758502. 978-1-4799-0540-9. (84-92).

    http://ieeexplore.ieee.org/document/6758502/

  • Jazizadeh F, Marin F and Becerik-Gerber B. (2013). A thermal preference scale for personalized comfort profile identification via participatory sensing. Building and Environment. 10.1016/j.buildenv.2013.06.011. 68. (140-149). Online publication date: 1-Oct-2013.

    https://linkinghub.elsevier.com/retrieve/pii/S0360132313001893

  • Pan D, Lam A and Wang D. Carrying my environment with me in iot-enhanced smart buildings. Proceeding of the 11th annual international conference on Mobile systems, applications, and services. (521-522).

    https://doi.org/10.1145/2462456.2465713

  • Taneja J, Krioukov A, Dawson-Haggerty S and Culler D. (2013). Enabling advanced environmental conditioning with a building application stack 2013 International Green Computing Conference (IGCC). 10.1109/IGCC.2013.6604519. 978-1-4799-0623-9. (1-10).

    http://ieeexplore.ieee.org/document/6604519/