Experiences with a high-fidelity wireless building energy auditing network
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Towards a zero-configuration wireless sensor network architecture for smart buildings
Proceedings of the First ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings
iSense: a wireless sensor network based conference room management system
Proceedings of the First ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings
sMAP: a simple measurement and actuation profile for physical information
Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems
ICCPS '12 Proceedings of the 2012 IEEE/ACM Third International Conference on Cyber-Physical Systems
BuildSys '12 Proceedings of the Fourth ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings
Thermovote: participatory sensing for efficient building HVAC conditioning
BuildSys '12 Proceedings of the Fourth ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings
SPOT: a smart personalized office thermal control system
Proceedings of the fourth international conference on Future energy systems
IAQSense: Indoor Air Quality Enhancement using Participatory-sensing
Proceedings of the 5th ACM Workshop on Embedded Systems For Energy-Efficient Buildings
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Commercial building is one of the major energy consumers that has drawn worldwide concerns. Heating, ventilating and air-conditioning (HVAC) system constitutes 40% of the total energy consumption in a typical commercial building. While the main objective of HVAC is to provide occupants with a comfort and safe environment, it currently lacks channels to recognize occupants' favourite temperatures as well as reflect their levels of comfort, e.g., too-cold or too-hot. Hence, it is hard to justify the energy consumption without considering end-user needs. Models of thermal comfort and predicted mean vote have been used to estimate such index, however, they are not widely adopted due to their complexity and inaccuracy. In this paper, we design the innovative system CarryEn, which first captures user's favourite temperature non-intrusively from their daily environment. We connect our system with the building management system (BMS), and optimize the setpoint temperature to occupants with our model. When the user moves into other rooms or buildings, his favourite setting will also be carried with him. Based on our experiments, CarryEn is able to achieve an improvement of 28.2% thermal satisfaction from occupants and save 13% of energy consumption.