Can HVAC really learn from users? A simulation-based study on the effectiveness of voting for comfort and energy use optimization

Agarwal, 2010, Occupancy-driven energy management for smart building automation Arsenio, 2014, 1 AMERICAN SOCIETY OF HEATING, REFRIGERATING AND AIR-CONDITIONING ENGINEERS, 2010 Boman, 1998, Energy saving and added customer value in intelligent buildings, International Conference on the Practical Application of Intelligent Agents and Multi-Agent Technology, Vol. 1, 505 Booy, 2008, A semiotic multi-agent system for intelligent building control Costa, 2015, 3I Buildings: Intelligent, interactive and immersive buildings, Procedia Engineering, 123, 7, 10.1016/j.proeng.2015.10.051 Daum, 2002, A personalized measure of thermal for building controls, Building and Environment, 46, 3, 10.1016/j.buildenv.2010.06.011 Davidsson, 2000, Saving energy and providing value added services in intelligent buildings: A MAS approach, Agent Systems, Mobile Agents, and Applications, 10.1007/978-3-540-45347-5_14 Davidsson, 2005, Distributed monitoring and control of office buildings by embedded agents, Information Sciences, 171, 293, 10.1016/j.ins.2004.09.007 Dawson-Haggerty, 2013, BOSS: Building operating system services, 443 Delaney, 2009, Evaluation of energy-efficiency in lighting systems using sensor networks Díaz, 2011, The ecosense project: An intelligent energy management system with a wireless sensor and actor network, Sustainability in Energy and Buildings, 7, 237, 10.1007/978-3-642-17387-5_24 Doctor, 2005, A fuzzy embedded agent-based approach for realizing ambient intelligence in intelligent inhabited environments, IEEE Transactions Systems, 35, 55 Dodier, 2006, Building occupancy detection through sensor belief networks, Energy and Buildings, 38, 1033, 10.1016/j.enbuild.2005.12.001 Dong, 2009, Sensor-based occupancy behavioral pattern recognition for energy and comfort management in intelligent buildings, 1444 Erickson, 2011, OBSERVE: Occupancy-based system for efficient reduction of HVAC energy Erickson, 2010 Erickson, 2009, Energy efficient building environment control strategies using real-time occupancy measurements Federspiel, 2003, Thermal comfort models and complaint frequencies, Center for the Built Environment Gao, 2009, The self-programming thermostat: Optimizing setback schedules based on home occupancy patterns Gunay, 2017 Hagras, 2004, Creating an ambient-intelligence environment using embedded agents, IEEE Intelligent Systems, 19, 12, 10.1109/MIS.2004.61 Hesse, 2001, Vol. 2 HUI, 2017, Major requirements for building smart homes in smart cities based on internet of things technologies, Future Generation Computer Systems, 76, 358, 10.1016/j.future.2016.10.026 Humphreys, 1998, Understanding the adaptive approach to thermal comforts, ASHRAE Technical Data Bulletin, 14 Jazizadeh, 2013, A thermal preference scale for personalized comfort profile identification via participatory sensing, Building and Environment, 68, 140, 10.1016/j.buildenv.2013.06.011 Kamthe, 2009, Scopes: Smart cameras object position estimation system, Wireless Sensor Networks, 279 Karjalainen, 2007, User problems with individual temperature control in offices, Building and Environment, 42, 10.1016/j.buildenv.2006.10.031 Kastner, 2010, Using AI to realize energy efficient yet comfortable smart homes Kim, 2008, Spotlight: Personal natural resource consumption profiler Klein, 2012, Coordinating occupant behavior for building energy and comfort management using multi-agent systems, Automation in Construction, 22, 525, 10.1016/j.autcon.2011.11.012 Lu, 2010, The smart thermostat: Using occupancy sensors to save energy in homes MacKay, 2003, 316 Mansur, 2014, The First International Conference on Cognitive Internet of Things Technologies, A Learning Approach for Energy Efficiency Optimization by Occupancy Detection. Accepted for Publication in COIOTE 2014 Mozer, 1998, The neural network House: An environment that adapts to its inhabitants, Artificial Intelligence, 110 Mozer, 2005, Lessions from an adaptive House, Smart Environments, 271, 10.1002/047168659X.ch12 Murakami, 2007, Field experiments on energy consumption and thermal comfort in the office environment controlled by occupants’ requirements from PC terminal, Building and Environment, 42, 4022, 10.1016/j.buildenv.2006.05.012 Oldewurtel, 2013, Importance of occupancy information for building climate control, Applied Energy - Sustainable Development of Energy, Water and Environment Systems, 101, 521 Padmanabh, 2009, iSense: A wireless sensor network based conference room management system, 37 Qiao, 2006, IEEE/WIC/ACM International Conference on Intelligent Agent Technology, A Multi-Agent System for Building Control, 653 Rashidi, 2010, Mining and monitoring patterns of daily routines for assisted living in real world settings Reinisch, 2010, 4th IEEE International Conference on Digital Ecosystems and Technologies, ThinkHome: A Smart Home as Digital Ecosystem, 256 Reinisch, 2011, ThinkHome energy efficiency in future smart homes, EURASIP Journal on Embedded Systems, 2011, 10.1155/2011/104617 Remagino, 2005, Ambient intelligence: A new multidisciplinary paradigm, IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 35, 1, 10.1109/TSMCA.2004.838456 Resendes, 2013, Conflict detection and resolution in home and building automation systems, Springer Journal of Ambient Intelligence and Humanized Computing, 5, 699, 10.1007/s12652-013-0184-9 Sierra, 2008, Intelligent Systems Applied to Optimize Building’S Environments Performance, 276, 237 Soucek, 2012, Current developments and challenges in building automation e & i, Elektrotechnik und Informationstechnik, 129, 278, 10.1007/s00502-012-0013-4 Wigginton, 2002 Yang, 2013, Development of multi-agent system for building energy and comfort management based on occupant behaviors, Energy and Buildings, 56, 1, 10.1016/j.enbuild.2012.10.025