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Machine Learning-Based Soft Sensors for the Estimation of Laundry Moisture Content in Household Dryer Appliances
Open AccessArticle

Laundry Fabric Classification in Vertical Axis Washing Machines Using Data-Driven Soft Sensors

1
Department of Information Engineering, University of Padova, 35131 Padova, Italy
2
Electrolux Italia S.p.a., PN 33080 Porcia, Italy
3
Human Inspired Technology Research Centre, University of Padova, 35121 Padova, Italy
*
Author to whom correspondence should be addressed.
Energies 2019, 12(21), 4080; https://doi.org/10.3390/en12214080
Received: 7 August 2019 / Revised: 15 October 2019 / Accepted: 21 October 2019 / Published: 25 October 2019
(This article belongs to the Special Issue Advanced Manufacturing Informatics, Energy and Sustainability)
Embedding household appliances with smart capabilities is becoming common practice among major fabric-care producers that seek competitiveness on the market by providing more efficient and easy-to-use products. In Vertical Axis Washing Machines (VA-WM), knowing the laundry composition is fundamental to setting the washing cycle properly with positive impact both on energy/water consumption and on washing performance. An indication of the load typology composition (cotton, silk, etc.) is typically provided by the user through a physical selector that, unfortunately, is often placed by the user on the most general setting due to the discomfort of manually changing configurations. An automated mechanism to determine such key information would thus provide increased user experience, better washing performance, and reduced consumption; for this reason, we present here a data-driven soft sensor that exploits physical measurements already available on board a commercial VA-WM to provide an estimate of the load typology through a machine-learning-based statistical model of the process. The proposed method is able to work in a resource-constrained environment such as the firmware of a VA-WM. View Full-Text
Keywords: household appliances; machine learning; regularization; soft sensors; sustainability; vertical axis washing machines household appliances; machine learning; regularization; soft sensors; sustainability; vertical axis washing machines
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MDPI and ACS Style

Maggipinto, M.; Pesavento, E.; Altinier, F.; Zambonin, G.; Beghi, A.; Susto, G.A. Laundry Fabric Classification in Vertical Axis Washing Machines Using Data-Driven Soft Sensors. Energies 2019, 12, 4080.

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