The smart thermostat: using occupancy sensors to save energy in homes
Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems
Carrying my environment with me in iot-enhanced smart buildings
Proceeding of the 11th annual international conference on Mobile systems, applications, and services
BOSS: building operating system services
nsdi'13 Proceedings of the 10th USENIX conference on Networked Systems Design and Implementation
Carrying My Environment with Me: A Participatory-sensing Approach to Enhance Thermal Comfort
Proceedings of the 5th ACM Workshop on Embedded Systems For Energy-Efficient Buildings
ZonePAC: Zonal Power Estimation and Control via HVAC Metering and Occupant Feedback
Proceedings of the 5th ACM Workshop on Embedded Systems For Energy-Efficient Buildings
A study towards applying thermal inertia for energy conservation in rooms
ACM Transactions on Sensor Networks (TOSN)
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Thermal comfort has traditionally been measured solely by temperature. While other methods such as Predicted Mean Vote (PMV) are available for measuring thermal comfort, the parameters required for an accurate value are overly complicated to obtain and require a great deal of sensory input. This paper proposes to bypass overly cumbersome or simplistic measures thermal comfort by bringing humans in the loop. By using humans as sensors, we can accurately adjust temperatures to improve occupant comfort. We show that occupants are more comfortable with a system that continually adjusts to thermal preference than a system that attempts to predict user comfort based on environmental factors. In addition, we also show that such a system is able to save 10.1% energy while improving the quality of service.