This award provides funding for a new institutional Computing Research Infrastructure (CRI) project focused on residential energy research at the University of Virginia. Recent studies have demonstrated great potential for applications of embedded sensing and control in the home environment. However, research in this area is limited by the inability to experiment beyond small scale field tests and pilot studies. The BetaHome Network is a new residential sensing testbed that includes an array of homes with extensive and semi-permanent instrumentation of the electrical, water, and HVAC systems. The testbed captures several dimensions of variability in homes that are not captured by one-off field tests and small pilot studies. Additionally, and perhaps most importantly, the BetaHome Network system tracks and records the locations of occupants within the home, in relation to the energy, water, and HVAC events that are also being recorded. This unique sensing testbed provides a complete, real-time picture of both occupancy and energy usage in the home with unprecedented detail about the internal happenings of the home. The testbed enables several new types of studies that were heretofore impractical, including cross-sectional analytics and controlled intervention studies. The project enables research on novel techniques for (i) occupancy and energy monitoring in homes (ii) personalized energy feedback (iii) intelligent thermostat control (iv) low-cost energy audits, and (v) intelligent fixture-driven water heating.
The research infrastructure created by this project enables research on new home monitoring and energy efficiency technologies, focusing on practical and low-cost solutions that can be readily translated to market. For example, preliminary studies demonstrated a 28% reduction per household in the energy required for heating and cooling, at the cost of only $25 in additional sensors per home. This project opens a new realm for residential ``living laboratories'' that enhance the infrastructure for research and education in the area of energy-efficient technologies, helping to propel the nation towards its goal of a 70% improvement in the total energy efficiency of existing buildings across the country by 2030. New courses are being developed as a result of this infrastructure and both graduate and undergraduate researchers are involved in new research. The project is producing a new data set of unprecedented detail that can be used as benchmarks for the energy monitoring community to enable research and inspire future generations of researchers to study science and engineering by illustrating its applied nature and potential for social benefit.
