ABSTRACT
To promote energy-saving behavior, disaggregating electricity usage is critical for increasing consumer awareness of energy usage behavior. This study proposes HeatProbe, a thermal-based power meter system that uses thermal imaging to track disaggregated appliance usage. We have designed, prototyped, and tested the HeatProbe system. Results show that HeatProbe successfully senses individual appliance operating durations with an average error of 125.03 seconds, achieving 80.2% appliance power accounting accuracy in different appliance usage scenarios.
Supplemental Material
- Behavior, Energy, and Climate Change Conference. http://www.beccconference.org.Google Scholar
- Gupta, S., Reynolds, M.S., and Patel, S.N. ElectriSense: Single-point Sensing using EMI for Electrical Event Detection and Classification in the Home. In Proc. Ubicomp 2010, ACM Press (2010), 139--148. Google ScholarDigital Library
- Kim, Y., Schmid, T., Charbiwala, Z.M., and Srivastava, M.B. ViridiScope: Design and Implementation of a Fine Grained Power Monitoring System for Homes. In Proc. Ubicomp 2009, ACM Press (2009), 245--254. Google ScholarDigital Library
- Rowe, A., Berges, M., and Rajkumar, R., Contactless Sensing of Appliance State Transitions. In Proc. BuildSys 2010, ACM Press (201 0), 19--24. Google ScholarDigital Library
- Cent-a-Meter, http://www.centameter.com.au.Google Scholar
- TED: The Energy Detective. http://www.theenergydetective.com.Google Scholar
- Jiang, X., Dawson-Haggerty, S., Dutta, P., and Culler, D. Design and Implementation of a High-fidelity AC Metering Network. In Proc. IPSN 2009, IEEE Computer Society (2009), 253--264. Google ScholarDigital Library
- Hart, G. Nonintrusive appliance load monitoring. In Proc. the IEEE, 80, 12 (1992), 1870--1891.Google ScholarCross Ref
- Norford, L. K. and Leeb, S. B. Non-intrusive electrical load monitoring in commercial buildings based on steady-state and transient load-detection algorithms. Energy and Buildings, 24, 1 (1996), 51--64.Google ScholarCross Ref
- Puri, C., Olson, L., Pavlidis, I., Levine, J., and Starren, J., StressCam: non-contact measurement of users' emotional states through thermal imaging. Ext. Abstracts CHI 2005, ACM Press (2005), 1725--1728. Google ScholarDigital Library
- Yun, C., Shastri, D., Pavlidis, I., and Deng, Z., O' game, can you feel my frustration?: improving user's gaming experience via stresscam. In Proc. CHI 2009, ACM Press (2009), 2195--2204. Google ScholarDigital Library
- Larson, E.C., Cohn, G., Gupta, S., Ren, X., Harrison, B., Fox, D. and Patel, S.N. HeatWave: Exploring the Feasibility of Thermal Imaging for Surface User Interaction, In Proc. CHI 2011, ACM Press (2011), 2565--2574. Google ScholarDigital Library
- Bayati, M., Shah, D., Sharma, M. Maximum Weight Matching via Max-Product Belief Propagation, In Proc. ISIT 2005, ARXIV (2005), 1763--176.Google ScholarCross Ref
- Bradski, G., Kaehler, A., Learning OpenCV: Computer Vision with the OpenCV Library, O'Reily Media (2008).Google Scholar
- Nilsson J. W., and Riedel S. Electric Circuits, 8th Edition, Prentice Hall (2007). Google ScholarDigital Library
- Patel, S.N., Gupta, S., Reynolds, M.S. The design and evaluation of an end-user-deployable, whole house, contactless power consumption sensor. In Proc. CHI 2010. ACM Press (2010), 2471--2480. Google ScholarDigital Library
- Stern, P.C. Information, incentives, and proenvironmental consumer behavior. Journal of Consumer Policy, 22, 4 (1999), 461--478.Google ScholarCross Ref
Index Terms
- HeatProbe: a thermal-based power meter for accounting disaggregated electricity usage
Recommendations
Demo: Nano Power Draw in Duty-Cycled Wireless Sensor Networks
WiNTECH '19: Proceedings of the 13th International Workshop on Wireless Network Testbeds, Experimental Evaluation & CharacterizationIn this work we present a novel power management architecture for Wireless Sensor Network devices towards minimizing the power consumption when nodes remain in sleep state. Specifically, we propose the employment of an on-board timer circuit that ...
eProfiler: High-Precision Power Monitoring System for IoT Devices Featuring Extreme Dynamic Range of Operation
ENSsys '20: Proceedings of the 8th International Workshop on Energy Harvesting and Energy-Neutral Sensing SystemsModern Internet-of-Things (IoT) devices and sensor systems exhibit extreme dynamic current consumption profile, since latest microprocessors and electronics support ultra-low currents in the sleep phase, of only a few nA, while they expend several mA in ...
Demo: In-situ Power Consumption Meter for Sensor Networks supporting Extreme Dynamic Range
WiNTECH '17: Proceedings of the 11th Workshop on Wireless Network Testbeds, Experimental evaluation & CHaracterizationTypical wireless sensor devices feature an extreme power consumption range between their active and sleep states, thus requiring different hardware setups for measuring their expenditure with high accuracy. In this demo paper we present the NITOS ...
Comments