Household Electrical Appliances Research Articles

Experimental study of energy efficiency of kitchen electrical appliances for boiling water

Introduction. Steady growth in the number of powerful electrical appliances and devices in households leads to an increase in electricity consumption. It significantly affects the economic costs of consumers and the deterioration of the ecological situation in the environment. Problem. The cost of electricity tariffs for the population tends to be relatively steadily increasing, which makes the issue of energy efficiency particularly relevant for consumers. The use of energy-efficient technologies in everyday life allows reducing electricity costs and increasing the economic efficiency of households. Energy efficiency of household electrical appliances is a pressing issue for ensuring a stable energy supply in the context of growing electricity consumption. Goal. An analytical study of the operating features of kitchen electrical appliances for boiling water and an experimental study of their energy efficiency. Methodology. The energy efficiency of the most common kitchen electrical appliances for boiling water was analyzed through experimental studies. Results. In terms of energy efficiency, the flow-through thermopot turned out to be the best among the studied electrical appliances, followed by an electric kettle and a traditional thermopot. Practical value. The use of energy-efficient technologies in modern household appliances is an important task, especially in winter and in conditions of shortage of electric power during military aggression from Russia and large-scale destruction of critical infrastructure and power facilities in our country. Further research will help reduce energy consumption and increase the energy efficiency of household appliances.

The problem of protecting a person from the effects of low-frequency electromagnetic fields in modern society. Possible ways to solve it

The paper considers the problem of the impact of low-frequency electromagnetic fields (EMF) generated by electric vehicles (EV) and household appliances on humans in modern society. The data on the effect of EMF on human health and regulatory documents establishing requirements for electromagnetic safety are presented. The method of electromagnetic shielding and materials for the implementation of this method are considered as a promising method for solving the problem. The levels of electromagnetic radiation from a number of EV and household electrical appliances have been experimentally measured. The efficiency of electromagnetic shielding of materials based on single-layer coatings of Ni80Fe20 alloys, multilayer film structures Ni80Fe20/Cu and amorphous metal alloys AMAG172 has been estimated using a computational method. It is shown that electromagnetic screens based on these materials significantly reduce the levels of exposure to EMF of EV and household electrical appliances on humans, which allows us to approach the hygienic standards recommended by doctors and meet the requirements of regulatory documents on remote control.

Combining an improved Apriori algorithm and Social Network analysis to identify the unique sequential features of individual household electricity consumption behaviours

ABSTRACT The household’s electricity consumption behaviour follows a unique sequential pattern and can be identified by analyzing the electricity consumption data with fine granularity in a smart home context. This particular sequence is concretely embodied in a series of electrical activities with temporal association relationships, thus forming a unique household electrical appliance activity-based chain (EAAC). In this study, we propose a method that combines an improved Apriori algorithm and Social Network to construct a household EAACs. First, we improved the Apriori algorithm (Apriori (1,1)) by combining the temporal and transactional sequences and used it to mine the time-series activity associations among different household appliances. After that, we used the Sliding Window concept to splice the time-series associations and obtain the unique EAACs for each household. Next, we visualized the EAACs using the Social Network analysis to reflect the unique sequential features of household electricity consumption behaviours. Finally, the model was validated by analyzing two families’ actual household electricity consumption data, and future research directions were given.

UTILISING FAILURE MODE AND EFFECT ANALYSIS AND THE KANO MODEL FOR INDUCTION STOVE PERFORMANCE IMPROVEMENT DURING INDONESIA’S ENERGY CONVERSION PROGRAM

In 2022, the Indonesian government, through the Indonesia State Electricity Company (PT. PLN), launched a program to shift from gas to electric induction stoves. This study analyzed induction stove failures, using data from 241 participants via WhatsApp Group (WAG) feedback. This research was combining Failure Mode and Effect Analysis (FMEA) and the KANO model to analyzing those failures and proposing the improvement. The failures that be prioritized for improvement were the monitor screen was off, the electricity was suddenly off, the stove went off when using the boiling function and the installation was inconvenient. Improvements were proposed to the program team, the stove producers and the community. This research finding offers insight for researchers and practitioners, namely enriching FMEA and KANO model integration for electric household appliances. These research findings also provide information on the use of induction stoves by the community for product improvements in subsequent programs.

Smart Home Automation System

This project introduces the overall framework of an economical wireless home automation system (HAS). Its primary emphasis lies in establishing an Internet of Things (IoT)-centered home automation setup, capable of automatic configuration based on environmental conditions and capable of overseeing multiple devices remotely via the internet. The objective is to design firmware for intelligent control, ensuring automated functionality with minimal human intervention to uphold the well-being of all electrical appliances in the household. Node MCU, a widely recognized open-source IoT platform, has been employed for the automation process. Various transmission modes are implemented across distinct system components to relay user commands from Node MCU to the actual device. The central control system utilizes wireless technology, enabling remote accessibility via a smartphone. The incorporation of a cloud server-based communication system enhances project practicality, providing users unrestricted access to appliances, regardless of their spatial proximity. To fortify automation, a data transmission network has been established. The user-friendly interface, cost-effective construction, and straightforward installation make it an ideal solution for managing household electrical appliances and devices. Both control and appliance status can be monitored through an Android platform. The system's objective is to enhance the living conditions of elderly and disabled individuals by offering necessary support and assistance, ultimately elevating the overall home living experience with the concept of a smart home.

SINUSOIDAL ELECTROMAGNETIC FIELD DECREASES OSTEOGENIC DIFFERENTIATION OF RAT BONE MARROW MESENCHYMAL STEM CELLS

Objective: The widespread use of household electrical appliances generating electric and magnetic fields was a significant focus of WHO attention because of its serious threat to human health, especially osteogenesis. This research investigated the effect of 50 Hz frequency (1 mT intensity) sinusoidal EMF (SEMF) on the osteogenic differentiation of rat bone marrow stem cells (rBMSCs) in vitro. Methods: Experimental groups were: positive control (cells cultured in osteogenic medium supplemented with 7-10 M Dexamethasone, negative control (cells cultured in α-MEM/10% FBS, 10 mmol Beta-Glycerol-Phosphate, 15% FBS, 50 ug/ml Ascorbic Acid bi-Phosphate, 100 unit/ml Penicillin) and for the EMF group, cells exposed to SEMF (50 Hz, 1 mT, 30 min/day) for 14 and 21 d. Alizarin red staining, Alkaline phosphatase activity, and QRT-PCR were performed. Results: The EMF group exhibited weaker positive stains for ALP and Alizarin red than the positive control group. The Runx2 and Ocn gene expression levels were significantly decreased compared to negative control at 14 and 21 d of EMF exposure, respectively. After 14 and 21 d of exposure, Runx2 and Ocn gene expression were much lower in the EMF group than in the positive control group. Conclusion: SEMF (1 mT, 50 Hz, 30 min/day) could retarded osteogenesis and reduce the osteogenic differentiation of rBMSCs.

Performance analysis of a blockchain enabled domestic power consumption monitoring and forecasting system

Purpose The purpose of this paper is to develop a blockchain-based data capture and transmission system that will collect real-time power consumption data from a household electrical appliance and transfer it securely to a local server for energy analytics such as forecasting. Design/methodology/approach The data capture system is composed of two current transformer (CT) sensors connected to two different electrical appliances. The CT sensors send the power readings to two Arduino microcontrollers which in turn connect to a Raspberry-Pi for aggregating the data. Blockchain is then enabled onto the Raspberry-Pi through a Java API so that the data are transmitted securely to a server. The server provides real-time visualization of the data as well as prediction using the multi-layer perceptron (MLP) and long short term memory (LSTM) algorithms. Findings The results for the blockchain analysis demonstrate that when the data readings are transmitted in smaller blocks, the security is much greater as compared with blocks of larger size. To assess the accuracy of the prediction algorithms data were collected for a 20 min interval to train the model and the algorithms were evaluated using the sliding window approach. The mean average percentage error (MAPE) was used to assess the accuracy of the algorithms and a MAPE of 1.62% and 1.99% was obtained for the LSTM and MLP algorithms, respectively. Originality/value A detailed performance analysis of the blockchain-based transmission model using time complexity, throughput and latency as well as energy forecasting has been performed.

SMART HOME MONITORING SYSTEM

The Project is about building a low-cost home automation system. It mainly focuses on creating an Internet based home automation system that can be automatically configured to run based on various conditions or that can be used to control multiple components through the internet. Wireless technology is used to enable remote access from a smartphone, PC, manually and voice command. The system is an accessible interface, affordable construction, and easy installation made it easier for controlling household electrical appliances and devices. The created system supports wireless control of lights, fans, air conditioners, televisions, Alarm, security cameras, electronic doors, computer systems, audio/visual devices, and more. It can be combined into a single portable unit. It is user friendly. Key Words: Wireless Control, Wi-Fi, Microcontroller, ESP RainMaker, Relay, Controlling of appliances, Monitoring.

AC-Duino Kit: Enhancing the Teaching and Learning Experience of Root-Mean-Square Current in Alternating Current through Arduino Microcontroller Application

Root-mean-square current in alternating current is an abstract concept that appears challenging to students in the absence of any hands-on experimental tool. Therefore, the AC-Duino Kit, utilising an Arduino Uno microcontroller and ACS712 current sensor, is developed and used in an experiential learning activity involving real-life household electrical appliances to enhance this topic's teaching and learning experience. Two-cycle action research was conducted on forty-six students undertaking a one-year matriculation program with data collected from document analysis, interview, and observation. The result shows that the students could relate root-mean-square current to power consumption, differentiate between heat and motor appliances, and relate peak current to electrical safety. The study confirmed that this activity could bridge the theoretical concept to real-life applications.

The Factors Affecting the Purchase Intention of Household Electrical Appliances (Home Appliances) That Are Good for Consumers’ Health in Chongqing City.

The objective of this study is to explore and examine the impact of these factors on the Purchase intention of household electrical appliances through the mediating role of Attitude. Survey data were collected from 329 consumers in Chongqing City. Results from the Partial Least Squares Structural Equation Modeling (SEM) using the Amos 20 program showed that Health concern, Environmental concern, Attitude, Perceived behavioral control, and Trust affect directly to purchasing intention of consumers. Results from the Process Macro using the SPSS 25 program have also identified the mediating role of Consumers’Attitudes in the relationship between Health Concern and Environmental Concern to Consumer’s Purchase intention. Finally, several suggested governance implications will assist manufacturers and marketers in developing targeted customer- focused strategies.

Electrical injuries in children—a 6-year retrospective study

BackgroundThis study aimed to assess the clinical epidemiological characteristics of children with electrical injuries and discuss the countermeasures for the prevention of electrical injuries in children. MethodsThe children with electrical injuries were grouped according to whether or not they were admitted to the hospital for treatment into inpatient and outpatient groups. Clinical data such as gender, causes of injury and injury-causing voltage distribution in different age groups were analyzed. The factors affecting hospitalization were subjected to χ2 test, Kruskal-Wallis H test, and logistic regression analysis. ResultsA total of 321 children were included with 37 divided into inpatient group and 284 divided into outpatient group. The incidence of electrical injuries was highest in children ≤6 years old and in the summer. There were significantly different in gender, place of occurrence, cause of injury and injury-causing voltage between the two groups (p < 0.05). Injury-causing voltage is an independent risk factor affecting hospitalization of children with electrical injuries (OR = 0.116, 95 %CI = 0.040–0.334, p = 0.000). In children ≤6 years old, boys suffered electrical injuries more frequently than girls; battery powered vehicle (47.53 %) was primarily the cause of injury; most of the patients (64.64 %) were exposed to low voltage below 100 Vs, mainly in the case of adolescent children. ConclusionMale preschoolers accounted for the majority of electrical injury cases, and these accidents mostly happened in household electrical appliances and household battery cars. Overall, it is necessary to improve family electrical safety education and reinforce protective measures against electric injury to children.

Assessment of Electromagnetic Shielding Efficacy of Magnetic Metal Oxide Nanoparticles and their Application in Electromagnetic Shielding Paints

AbstractPeople are continuously exposed to electromagnetic waves emitted by mobile phones, base stations, computers, household electrical appliances, and nearby devices. Shielding against electromagnetic radiation is of great importance to avoid potential adverse effects on human health. This study addresses the development of electromagnetic shielding paints containing magnetic metal oxide nanoparticles. Magnetic metal oxide nanoparticles with a spinel ferrite structure, namely Fe3O4, CoFe2O4, and SnFe2O4, were synthesized using the co‐precipitation method. Their structural, morphological, and magnetic properties were characterized through FTIR, XRD, TEM, and VSM measurements. Electromagnetic shielding efficacy was assessed within the 3.5–12.5 GHz frequency range using waveguide measurements. Notably, pure magnetic metal oxide nanoparticles exhibited limited shielding efficiency, but incorporating conductive materials like multi‐walled carbon nanotubes improved the efficacy. Optimization studies, involved adjusting the nanoparticle‐to‐carbon nanotube ratios and coating thickness, demonstrated the best shielding to be with 50 : 10 [MFe2O4:PEG]:mwcnt ratio (M : Fe, Co, Sn) and 0.720 mm thickness, achieving up to 99 % of radiation shielding. The subsequent incorporation of the optimized magnetic composites into a water‐based wall paint at a 1 : 2 weight ratio demonstrated their effectiveness in shielding, successfully blocking 84 % of incoming radiation.

New Issues on Electromagnetic Biocompatibility

The paper presents some aspects on the concept of electromagnetic biocompatibility (EMBC), fully supported by epidemiological studies and in the same time by the latest document of the SCENIHR (an organism of the European Commission), regarding extremely low frequency magnetic fields. Modern life is full of artificially generated electric and magnetic fields. We are always exposed to those electromagnetic fields composed of various frequency components. One of these sources is represented by the frequency of 50Hz, the electric power frequency of commercial power transmission and distribution and of household electric appliances. It can be mentioned also high frequencies near 1GHz for cellular phones, and other intermediate frequencies for various appliances. The authors, adepts of the prudential avoidance policy, present several examples of possible harmful effects determined by extremely low frequency magnetic fields, dedicated to building services engineering in residences and in the industrial environment, along with several methods of mitigating them.

Enhancing Residential Electricity Safety and Management: A Novel Non-Intrusive Load Monitoring-Based Methodology for Accurate Appliance Operational State Identification

Non-intrusive load monitoring (NILM) technology, crucial for intelligent electricity management, has gained considerable attention in residential electricity usage studies. NILM enables monitoring of total electrical current and voltage in homes, offering insights vital for enhancing safety and preventing domestic electrical accidents. Despite its importance, accurately discerning the operational status of appliances using non-intrusive methods remains a challenging area within this field. This paper presents a novel methodology that integrates an advanced clustering algorithm with a Bayesian network for the identification of appliance operational states. The approach involves capturing the electrical current signals during appliance operation via NILM, followed by their decomposition into odd harmonics. An enhanced clustering algorithm is then employed to ascertain the central coordinates of the signal clusters. Building upon this, a three-layer Bayesian network inference model, incorporating leak nodes, is developed. Within this model, harmonic signals are used as conditions for node activation. The operational states of the appliances are subsequently determined through probabilistic reasoning. The proposed method’s effectiveness is validated through a series of simulation experiments conducted in a laboratory environment. The results of these experiments (low mode 89.1%, medium mode 94.4%, high mode 92.0%, and 98.4% for combination) provide strong evidence of the method’s accuracy in inferring the operational status of household electrical appliances based on NILM technology.

Design of a mini hydro-electric power plant

The core concept of hydropower centers on capturing the energy produced as water moves from a higher elevation to a lower one. This involves utilizing the resulting water pressure to generate electrical energy. This practical application of hydropower generation theory entails the design and installation of a mini hydropower plant. To assess its performance, a storage tank was strategically positioned at the maximum height to optimize water pressure, and a plastic pipe was employed for transportation. The construction of a turbine and generator, along with the subsequent assembly of their respective components, constitutes the formation of the hydropower plant. The hydro turbine converts water pressure into mechanical shaft power, propelling the electric generator. The outcome is an alternating electromotive force (e.m.f) of 210 Volts at a frequency of 50 Hz, suitable for powering various household electrical appliances.

An Eye Tracking and Brain–Computer Interface-Based Human–Environment Interactive System for Amyotrophic Lateral Sclerosis Patients

Amyotrophic Lateral Sclerosis (ALS) patients suffer a great inconvenience in their daily lives due to the gradual loss of their motion abilities. In order to help ALS patients regain their self-care abilities at a certain level, an eye-tracking and brain-computer interface (BCI) based human-environment interactive (HEI) system is proposed. Through a single-channel EEG recorder and a pair of eye-tracking glasses, the user’s attention levels and gaze points are detected. Based on the two types of intention information, the target objects are recognized by a YOLOv5 (You Only Look Once v5) model. Then according to voice instructions, users can control the household electric appliances. The system performed a high success rate of 89.3% experimentally, providing a reliable and capable assistive solution for ALS patients.

Application Analysis of DCF Model in Enterprise Value Evaluation: A Case Study of Midea

With the development of markets of household electric appliances and the extinct sales performance of Midea, Midea should be viewed as a good example to explore. Many company values are overstated or understated, which has caused major problems for the stability of markets. Therefore, the author made an effort to determine the company's value so that it could be compared to its market capitalization to determine whether it is underpriced or overpriced. And in order to do that, the company was examined using the discounted cash flow (DCF) model. It was discovered that the market price of Midea should be around 384.92 billion CNY, which is slightly higher than its actual market capitalisation. As a result, although there might be some deviations made by some other factors, that might indicate that Midea has been marginally underpriced in the market.

(Invited) self-Powered Multifunctional Sensing and Control for Smart Wearables and Human-Machine Interfaces

Robust, high-performance tactile sensors are critical for developing soft intelligent robotics, human-machine interfaces (HMI), and wearable electronics. However, it is challenging to fabricate soft tactile sensors capable of multifunctional sensing under both fast and slow response conditions in a simple and low-cost manner. In this talk, I will present our recent efforts in developing novel self-powered sensors and HMIs for wearables and intelligent controls. I will first introduce a textile-based tactile sensor capable of multifunctional sensing (covering both dynamic and static measurements) for personalized healthcare monitoring and soft robotic control. Inspired by human skin, the tactile sensor consists of a triboelectric nanogenerator sensing layer to mimic the function of fast-adapting (FA) mechanoreceptors and a piezoresistive sensing layer to achieve the functionality of slow-adapting (SA) mechanoreceptors. Then, I will demonstrate a self-powered breath sensor to monitor the health conditions of patients and provide daily assistance for severely disabled people to control electrical household appliances and other smart systems. The new system provides the advantages of high sensitivity, good stability, low cost, and ease of use.

Training On Repairing Household Electrical Equipment In Pare Pare Community, South Sulawesi

This community service activity was carried out for the people of Pare Pare South Sulawesi. This service activity is carried out in the form of training in the maintenance and repair of household electrical appliances. The purpose of this community service activity is to provide community service by providing training on: how to maintain household electrical appliances in general, diagnose damage, and repair damage based on diagnosis. Materials provided in this training include: maintenance of household electrical appliances, repair of damage to household electrical appliances, operation of household electrical appliances, and installation of household electrical devices. The implementation of community service regarding household electrical appliances ran smoothly. This community service activity has yielded results; increasing participants' knowledge of the benefits of maintaining electrical appliances, increasing participants' knowledge of damage diagnosis, and increasing participants' knowledge of correct repairs of household electrical appliances..

The determinants of household electricity demand in Turkey: An implementation of the Heckman Sample Selection model

Residential areas have a significant share in electrical energy consumption in Turkey. At this point, determining electricity consumption demand in residential areas will significantly contribute to ensuring energy efficiency throughout the country. Accurate econometric modelling of the relationships between the various socio-economic characteristics of households and their energy consumption/expenditure can serve as a basis for policymakers when planning investments aimed at efficiency on primary energy consumption in residences. Considering these issues, this study aims to examine the electricity consumption demand in residential areas in Turkey in terms of various socio-economic and building and property characteristics variables. At this point, the fact that some households have zero electricity consumption has led to the need to use censored regression models. The Heckman Sample Selection model was used, which makes it possible to estimate the consumption decision of individuals in two stages and eliminates the parameter bias problem caused by linear regression analysis. Heckman Sample Selection modelling was carried out in the study using Turkish Statistical Institute (TURKSTAT) 2019 Household Budget Survey data. According to the results, it has been determined that annual disposable income, various demographic variables (age, education level, marital status), characteristics of the house (size) and the presence of various electrical household appliances (air conditioner, tumble dryer, deep freezer) have significant effects on electricity consumption. The systematic preparation of informative brochures on the effective use of household electrical appliances can significantly contribute to efficiency. In addition, in countries like Turkey that depend on foreign energy, providing incentives towards renewable energy sources is considered necessary to contribute to the country's economy positively.