Smart * : An Open Data Set and Tools for Enabling Research in Sustainable Homes

The goal of the Smart* project is to optimize home energy consumption. As part of the project, we have designed and deployed a “live” system that continuously gathers a wide variety of environmental and operational data in three real homes. In contrast to prior work, our focus has been on sensing depth, i.e., collecting as much data as possible from each home, rather than breadth, i.e., collecting data from as many homes as possible. Our data captures many important aspects of the home environment, including average household electricity usage every second, as well as usage at every circuit and nearly every plug load, electricity generation data from on-site solar panels and wind turbines, outdoor weather data, temperature and humidity data in indoor rooms, and, finally, data for a range of important binary events, e.g., at wall switches, the HVAC system, doors, and from motion sensors. We also have electricity usage data every minute from 400 anonymous homes. This data corpus has served as the foundation for much of our recent research. In this paper, we describe our data sets as well as basic software tools we have developed to facilitate their collection. We are releasing both the data and tools publicly to the research community to foster future research on designing sustainable homes.

[1]  G.W. Hart,et al.  Residential energy monitoring and computerized surveillance via utility power flows , 1989, IEEE Technology and Society Magazine.

[2]  Mani B. Srivastava,et al.  ViridiScope: design and implementation of a fine grained power monitoring system for homes , 2009, UbiComp.

[3]  Prashant J. Shenoy,et al.  Private memoirs of a smart meter , 2010, BuildSys '10.

[4]  Prashant J. Shenoy,et al.  Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems , 2010, 2010 7th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON).

[5]  Prashant J. Shenoy,et al.  The case for efficient renewable energy management in smart homes , 2011, BuildSys '11.

[6]  Prashant J. Shenoy,et al.  Predicting solar generation from weather forecasts using machine learning , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[7]  Catherine Rosenberg,et al.  Markovian models for home electricity consumption , 2011, GreenNets '11.

[8]  Kamin Whitehouse,et al.  The hitchhiker's guide to successful residential sensing deployments , 2011, SenSys.

[9]  Prashant J. Shenoy,et al.  Exploiting home automation protocols for load monitoring in smart buildings , 2011, BuildSys '11.

[10]  J. Zico Kolter,et al.  REDD : A Public Data Set for Energy Disaggregation Research , 2011 .

[11]  Prashant J. Shenoy,et al.  SmartCharge: Cutting the electricity bill in smart homes with energy storage , 2012, 2012 Third International Conference on Future Systems: Where Energy, Computing and Communication Meet (e-Energy).

[12]  Prashant J. Shenoy,et al.  SmartCap: Flattening peak electricity demand in smart homes , 2012, 2012 IEEE International Conference on Pervasive Computing and Communications.