The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
ElectriSense: single-point sensing using EMI for electrical event detection and classification in the home
Abstract
This paper presents ElectriSense, a new solution for automatically detecting and classifying the use of electronic devices in a home from a single point of sensing. ElectriSense relies on the fact that most modern consumer electronics and fluorescent lighting employ switch mode power supplies (SMPS) to achieve high efficiency. These power supplies continuously generate high frequency electromagnetic interference (EMI) during operation that propagates throughout a home's power wiring. We show both analytically and by in-home experimentation that EMI signals are stable and predictable based on the device's switching frequency characteristics. Unlike past transient noise-based solutions, this new approach provides the ability for EMI signatures to be applicable across homes while still being able to differentiate between similar devices in a home. We have evaluated our solution in seven homes, including one six-month deployment. Our results show that ElectriSense can identify and classify the usage of individual devices with a mean accuracy of 93.82%.
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Cites
Nonintrusive appliance load monitoring
Hart, G. W. (1992) · Proceedings of the IEEE · doi:10.1109/5.192069 · Cited by 3,165
Patel, S., Robertson, T. M., Kientz, J. A., Reynolds, M. S., & Abowd, G. D. (2007) · Ubiquitous Computing · doi:10.5555/1771592.1771608 · Cited by 331
Self-citationSensing from the basement: a feasibility study of unobtrusive and low-cost home activity recognition
Fogarty, J., Au, C., & Hudson, S. E. (2006) · Proceedings of the 19th annual ACM symposium on User interface software and technology · doi:10.1145/1166253.1166269 · Cited by 230
Bathroom Activity Monitoring Based on Sound
Chen, J., Kam, A. H., Zhang, J., Liu, N., & Shue, L. (2005) · Lecture Notes in Computer Science · doi:10.1007/11428572_4 · Cited by 202
HydroSense: infrastructure-mediated single-point sensing of whole-home water activity
Froehlich, J. E., Larson, E., Campbell, T., Haggerty, C., Fogarty, J., & Patel, S. N. (2009) · Proceedings of the 11th international conference on Ubiquitous computing · doi:10.1145/1620545.1620581 · Cited by 182
Self-citationPowerLine Positioning: A Practical Sub-Room-Level Indoor Location System for Domestic Use
Patel, S., Truong, K. N., & Abowd, G. D. (2006) · Lecture notes in computer science · doi:10.1007/11853565_26 · Cited by 125
Self-citationPatel, S., Reynolds, M. S., & Abowd, G. D. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-79576-6_1 · Cited by 121
Self-citationA Platform for Ubiquitous Sensor Deployment in Occupational and Domestic Environments
Lifton, J. H., Feldmeier, M., Ono, Y., Lewis, C., & Paradiso, J. A. (2007) · ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) · doi:10.1109/ipsn.2007.4379671 · Cited by 115
The Design of a Portable Kit of Wireless Sensors for Naturalistic Data Collection
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GasSense: Appliance-Level, Single-Point Sensing of Gas Activity in the Home
Cohn, G. A., Gupta, S., Froehlich, J. E., Larson, E. C., & Patel, S. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-12654-3_16 · Cited by 64
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Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey
Zoha, A., Gluhak, A., Imran, M., & Rajasegarar, S. (2012) · Sensors · doi:10.3390/s121216838 · Cited by 954
Is disaggregation the holy grail of energy efficiency? The case of electricity
Carrie Armel, K., Gupta, A., Shrimali, G., & Albert, A. (2013) · Energy Policy · doi:10.1016/j.enpol.2012.08.062 · Cited by 595
Toward Non-Intrusive Load Monitoring via Multi-Label Classification
Tabatabaei, S. M., Dick, S., & Xu, W. (2017) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2016.2584581 · Cited by 304
Metadata
- Authors
- Gupta, S., Reynolds, M. S., & Patel, S. N.
- Venue
- Proceedings of the 12th ACM international conference on Ubiquitous computing
- Publisher
- ACM
- Published
- 2010-09-26
- Pages
- 139-148
- OpenAlex
- W2161708246
- Cited by
- 422
- References
- 10
- FWCI
- 37.56
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: ElectriSense: single-point sensing using EMI for electrical event detection and classification in the home. https://app.cochat.ai/papers/10.1145/1864349.1864375
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- Gupta, S., Reynolds, M. S., & Patel, S. N. (2010). ElectriSense: single-point sensing using EMI for electrical event detection and classification in the home. Proceedings of the 12th ACM international conference on Ubiquitous computing. https://doi.org/10.1145/1864349.1864375
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
