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Open AccessArticle

Multimodal Utility Data for Appliance Recognition: A Case Study with Rule-Based Algorithms

by Arkadiusz Orłowski, Krzysztof Gajowniczek, Marcin Bator and Robert Budzyński

Sensors 2026, 26(2), 527; https://doi.org/10.3390/s26020527 - 13 Jan 2026

Viewed by 614

Appliance recognition from aggregate household measurements is challenging under real deployment conditions, where multiple devices operate concurrently and sensor data are affected by imperfections such as noise, missing samples, and nonlinear meter response. In contrast to many studies that rely on curated or idealized datasets, this work investigates appliance recognition using real multimodal utility data (electricity, water, gas) collected at the building entry point, in the presence of substantial uninstrumented background activity. We present a case study evaluating transparent, rule-based detectors designed to exploit characteristic temporal dependencies between modalities while remaining interpretable and robust to sensing imperfections. Four household appliances—washing machine, dishwasher, tumble dryer, and kettle—are analyzed over six weeks of data. The proposed approach achieves reliable detection for structured, water-related appliances (22/30 washing cycles, 19/21 dishwashing cycles, and 23/27 drying cycles), while highlighting the limitations encountered for short, high-power events such as kettle usage. The results illustrate both the potential and the limitations of conservative rule-based detection under realistic conditions and provide a well-documented baseline for future hybrid systems combining interpretable rules with data-driven adaptation. Full article

(This article belongs to the Special Issue Multimodal Sensing Technologies for IoT and AI-Enabled Systems)

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25 pages, 3159 KB

Open AccessArticle

A Genetic Algorithm-Based Home Energy Management Framework for Optimizing User-Dependent Flexible Loads

by João Tabanêz Patrício, Francisco Januário Silva, Rui Amaral Lopes, Nuno Amaro and João Martins

Energies 2026, 19(1), 80; https://doi.org/10.3390/en19010080 - 23 Dec 2025

Cited by 2 | Viewed by 1054

Abstract

This paper presents a Genetic Algorithm-based Home Energy Management System designed to exploit the energy flexibility of user-dependent loads by identifying and recommending optimal operating schedules that minimize electricity costs. To determine the most advantageous 15 min activation slot for the following day for each load, the algorithm uses as input the forecasted consumption profile of non-optimizable loads and photovoltaic generation, both obtained through an LSTM-based model, along with the contracted power, applicable tariffs, and the load profiles of the selected appliances. Unlike previous approaches, the proposed framework allows users to select which loads to optimize and define specific operational constraints. Additionally, a user-friendly interface was developed to facilitate seamless interaction between the user and the system. To validate the proposed framework, a case study was conducted on a residential household with four occupants located in Portugal, considering user-dependent flexible loads such as a washing machine, tumble dryer, and dishwasher. The results demonstrated that the developed system operated effectively, reducing electricity costs by approximately 9% compared to a scenario without the proposed solution. Full article

(This article belongs to the Section G: Energy and Buildings)

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17 pages, 4223 KB

Open AccessFeature PaperArticle

The Toxicity of Polyester Fibers in Xenopuslaevis

by Renato Bacchetta, Anna Winkler, Nadia Santo and Paolo Tremolada

Water 2021, 13(23), 3446; https://doi.org/10.3390/w13233446 - 4 Dec 2021

Cited by 22 | Viewed by 5813

Abstract

Microplastics are practically ubiquitous and pose a serious survival challenge for many species. Most of the exposure experiments for determining the toxicological effects of microplastics were performed with a microplastic varying little in shape and size (often purchased microplastic beads), but few studies deal with non-homogeneous samples. We analyzed the effect on Xenopuslaevis larva on the early development of polyester fibers, PEFs, taken from a dryer machine in which 100% polyester fabrics were dried after washing. Three concentrations were tested. The results showed that the gastrointestinal tract, GIT, was the most affected system by PEFs which modified the normal shape of the intestine with an EC₅₀ 96 h value of 6.3 µg mL⁻¹. Fibers were observed to press against the digestive epithelium, deforming the normal architecture of the gut, sometimes pushing deep into the epithelium until piercing it. Physical GIT occlusion was observed in a concentration-dependent manner. However, no other damages were registered. No mortality was observed, but PEF-exposed larvae showed a significant reduction in their mobility. The results of the present paper suggest that environmental samples with their heterogeneity may have adverse effects on X. laevis development. Full article

(This article belongs to the Special Issue Analysis and Prevention of Microplastics Pollution in Water: Current Research and Future Directions)

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28 pages, 9211 KB

Open AccessArticle

Performance of the Condensation Process for Water Vapour in the Presence of a Non-Condensable Gas on Vertical Plates and Horizontal Tubes

by Primož Poredoš, Nada Petelin, Tilen Žel, Boris Vidrih, Pero Gatarić and Andrej Kitanovski

Energies 2021, 14(8), 2291; https://doi.org/10.3390/en14082291 - 19 Apr 2021

Cited by 10 | Viewed by 5210

Abstract

The condensation of humid air is a crucial step in air conditioning and process engineering. However, the models that describe the condensation of vapour in the presence of a non-condensable gas require time-consuming numerical calculations that go beyond the Nusselt film theory. Only a small number of publications exist, where simple and computationally effective correlations for the condensation of water vapour in the presence of air are presented for specially designed condenser heat exchangers. Therefore, the objective of this paper is to extend the existing semi-empirical correlations for different geometries and process parameters. For the purpose of the study, an experimental setup with two different condenser heat exchangers based on vertical plates (height 74 mm) and horizontal tubes (3 tubes, diameter 40 mm and 7 tubes, diameter 15 mm) was built. Additionally, based on existing correlations, we developed two semi-empirical models that predict the condensation mass flux for the proposed geometries. Here, we report that the agreement between the experimental and theoretical values predicted by the new, semi-empirical correlations is excellent, with an average uncertainty of less than ±6%. Their usability was demonstrated by a possibly significant performance improvement of the condenser inside a condensation-type tumble dryer. Full article

(This article belongs to the Special Issue Heat Exchangers: Cooling and Heating Systems)

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16 pages, 907 KB

Open AccessArticle

Effect of Sampling Rate on Photovoltaic Self-Consumption in Load Shifting Simulations

by Philippe Voinov, Patrick Huber, Alberto Calatroni, Andreas Rumsch and Andrew Paice

Energies 2020, 13(20), 5393; https://doi.org/10.3390/en13205393 - 15 Oct 2020

Cited by 4 | Viewed by 6437

Abstract

Grid-connected photovoltaic (PV) capacity is increasing and is currently estimated to account for 3.0% of worldwide energy generation. One strategy to balance fluctuating PV power is to incentivize self-consumption by shifting certain loads. The potential improvement in the amount of self-consumption is usually estimated using smart meter and PV production data. Smart meter data are usually available only at sampling frequences far below the Nyquist limit. In this paper we investigate how this insufficient sampling rate affects the estimated self-consumption potential of shiftable household appliances (washing machines, tumble dryers and dishwashers). We base our analyses on measured consumption data from 16 households in the UK and corresponding PV data. We found that the simulated results have a marked dependence on the data sampling rate. The amount of self-consumed energy estimated with data sampled every 10 min was overestimated by 30–40% compared to estimations using data with 1 min sampling rate. We therefore recommend to take this factor into account when making predictions on the impact of appliance load shifting on the rate of self-consumption. Full article

(This article belongs to the Special Issue Analysis of Solar Photovoltaic Self-Consumption)

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14 pages, 1165 KB

Open AccessData Descriptor

Residential Power Traces for Five Houses: The iHomeLab RAPT Dataset

by Patrick Huber, Melvin Ott, Martin Friedli, Andreas Rumsch and Andrew Paice

Data 2020, 5(1), 17; https://doi.org/10.3390/data5010017 - 5 Feb 2020

Cited by 16 | Viewed by 5683

Abstract

Datasets with measurements of both solar electricity production and domestic electricity consumption separated into the major loads are interesting for research focussing on (i) local optimization of solar energy consumption and (ii) non-intrusive load monitoring. To this end, we publish the iHomeLab RAPT dataset consisting of electrical power traces from five houses in the greater Lucerne region in Switzerland spanning a period from 1.5 up to 3.5 years with a sampling frequency of five minutes. For each house, the electrical energy consumption of the aggregated household and specific appliances such as dishwasher, washing machine, tumble dryer, hot water boiler, or heating pump were metered. Additionally, the data includes electric production data from PV panels for all five houses, and battery power flow measurement data from two houses. Thermal metadata is also provided for the three houses with a heating pump. Full article

(This article belongs to the Special Issue Data Sensing and Analysis in Design, Construction, Operation, Monitoring, and Maintenance of Built Environments)

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