Next Article in Journal
Improving the Performance of Pseudo-Random Single-Photon Counting Ranging Lidar
Next Article in Special Issue
eHomeSeniors Dataset: An Infrared Thermal Sensor Dataset for Automatic Fall Detection Research
Previous Article in Journal
Prototyping a System for Truck Differential Lock Control
Previous Article in Special Issue
A Multi-Agent Gamification System for Managing Smart Homes
Open AccessArticle

Nonintrusive Appliance Load Monitoring: An Overview, Laboratory Test Results and Research Directions

1
Institute of Radioelectronics and Multimedia Technologies, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warsaw, Poland
2
Institute of Electrical Power Engineering, Warsaw University of Technology, Koszykowa 75, 00-662 Warsaw, Poland
*
Authors to whom correspondence should be addressed.
Sensors 2019, 19(16), 3621; https://doi.org/10.3390/s19163621
Received: 12 July 2019 / Revised: 6 August 2019 / Accepted: 17 August 2019 / Published: 20 August 2019
(This article belongs to the Special Issue Sensor Technology for Smart Homes)
Nonintrusive appliance load monitoring (NIALM) allows disaggregation of total electricity consumption into particular appliances in domestic or industrial environments. NIALM systems operation is based on processing of electrical signals acquired at one point of a monitored area. The main objective of this paper was to present the state-of-the-art in NIALM technologies for the smart home. This paper focuses on sensors and measurement methods. Different intelligent algorithms for processing signals have been presented. Identification accuracy for an actual set of appliances has been compared. This article depicts the architecture of a unique NIALM laboratory, presented in detail. Results of developed NIALM methods exploiting different measurement data are discussed and compared to known methods. New directions of NIALM research are proposed. View Full-Text
Keywords: NIALM; smart home; electrical appliances; home events; load disaggregation; sensing technologies; intelligent algorithms; human behavior NIALM; smart home; electrical appliances; home events; load disaggregation; sensing technologies; intelligent algorithms; human behavior
Show Figures

Figure 1

MDPI and ACS Style

Wójcik, A.; Łukaszewski, R.; Kowalik, R.; Winiecki, W. Nonintrusive Appliance Load Monitoring: An Overview, Laboratory Test Results and Research Directions. Sensors 2019, 19, 3621.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop