Humans spend 90% of their lives inside buildings, but often the Heating, Ventilation, and Air Conditioning (HVAC) systems of commercial buildings do not properly maintain occupant comfort. Use of feedback through comfort voting applications has been shown to improve the quality of service, but the effects of application feedback and user interface design has not been investigated. In this work, we present several methods of feedback that use data presentation and environmental interaction in comfort voting applications. Through a 40 week user study of 61 University employees across 3 buildings, we show that feedback systems can be used to increase user satisfaction with thermal conditions from 33.9% to 93.3% and reduce energy consumption up to 18.99% compared to a system without voting. In addition, we find that by including a drifting control strategy, we find energy savings up to 37% can be realized without a significant reduction in satisfaction.

We present a holistic architecture for energy management in sensor networks. Our architecture is based on a model-driven approach which attempts to (a) establish functional relationships across different components of the software stack and the interrelated parameters based on empirical data, (b) use the maximum sensor value and time-synchronization errors acceptable by the users of the sensor network application as input to establish minimum quality of service requirements, and (c) optimize the parameter values of all the software modules within the node's application stack to minimize total energy consumption for each sensor node. We explore the trade-offs of the design space by using a non-trivial application that includes sensing, time synchronization and routing modules and show that when using our architecture, we can provide energy savings in the average of 37% to 76% while still maintaining quality of service both in terms of the expected sensing and time-synchronization errors. We further show that even when using modules that perform significantly better than others with default values (e.g. ORW >> CTP), we can still reduce overall energy consumption by properly adjusting the parameters of lowest performance modules and provide energy savings in the average of 30% to 43%.

Buildings are often inefficiently conditioned. Rooms that are empty are needlessly conditioned and partially filled rooms are conditioned assuming maximum occupancy. In this demonstration, we describe a system that reduces energy consumption by opportunistically reducing energy consumption based on room usage; we only condition rooms currently occupied and condition the space based on real-time occupancy measurements. We will show how a thermal sensor array can be used measure occupancy in real-time and how this occupancy information can be integrated with a real building management system in order to control the heating, cooling, ventilation and lighting of a building to optimize energy usage.