Building Energy Monitoring and Control using Wireless Sensor Networks
The ultimate goal of this dissertation is to develop the required network and systems-level software to support distributed monitoring and control using the resource constrained platforms used in wireless sensor networks. We use a building energy monitoring and control application to demonstrate the usefulness of our system. Building energy management is necessary to tailor building performance to the occupant rather than forcing the occupant to change their behavior in order to conserver energy. Wireless sensor networks are a good fit to solve this problem because they can be used to create low-cost communication networks. These networks can be used to share information between separate systems. However, current wireless sensor network architectures and systems have focused on centralized systems with less emphasis on peer to peer information sharing.
Our main contributions are in two distinct areas. 1) WSN networking and systems. We are developing a complete WSN architecture that is better optimized for the problem of distributed monitoring and control using peer to peer communication. Central to our approach is a novel multicast implementation for IPv6 WSNs that we have developed. Using multicast communication allows sensor nodes to efficiently share data in a distributed fashion while the use of standard IPv6 communication greatly improves interoperability. 2) Building energy management. Previous studies of building energy consumption have focused on large appliances and group all small devices into the category of miscellaneous electrical loads. By embracing WSN-based monitoring and developing improved non-intrusive load monitoring techniques for these devices we are able to provide a more detailed analysis of building energy consumption and how human behaviors affect consumption. Our preliminary studies have demonstrated a 7%-14% reduction in energy consumption using a distributed WSN-based control system.
- Alan Marchiori, William Navidi, Leiko Earle, and Qi Han, Building the case for automated building energy management, ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings (BuildSys), in conjunction with ACM SenSys, Toronto, Canada, November 6, 2012.
View the data here.
- Alan Marchiori, Doug Hakkarinen, Qi Han, and Leiko Earle, Circuit-Level Load Monitoring for Household Energy Management, IEEE Pervasive Computing, Special Issue on Smart Energy Systems, Vol. 10, No. 1, January-March 2011.
- Alan Marchiori, Network and Systems Support for Building Energy Monitoring and Control using Wireless Sensor Networks, Ph.D dissertation, Colorado School of Mines, 2011
- Alan Marchiori and Qi Han, PIM-WSN: Efficient Multicast for IPv6 Wireless Sensor Networks, The 12th IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks (WoWMoM), 2011.
- Alan Marchiori and Qi Han, Distributed Wireless Control for Building Energy Management, ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings (BuildSys), in conjunction with ACM SenSys, Zurich, Switzerland, November 2010.
View the Mote Designs here.
- Alan Marchiori and Qi Han, Using Circuit-Level Power Measurements in Household Energy Management Systems, ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings (BuildSys) in conjunction with ACM SenSys, Berkeley, California, November 2009. Best Paper Award.
- Alan Marchiori and Qi Han, A Two-stage Bootloader to Support Multi-application Deployment and Switching in Wireless Sensor Networks, IEEE International Conference on Embedded and Ubiquitous Computing (EUC), Vancouver, Canada, August 2009.
- Alan Marchiori and Qi Han, A Foundation for Interoperable Sensor Networks with Internet Bridging, The Fifth Workshop on Embedded Networked Sensors (HotEmNets), June 2008
This work was supported in part by NSF grant CNS-0855060 and the U. S. Department of Energy (through the National Renewable Energy Laboratory under contract number DE-AC36-08GO28308).