Status Of Appliances Research Articles

Towards Dynamic Coordination Among Home Appliances Using Multi-Objective Energy Optimization for Demand Side Management in Smart Buildings

In this paper, we propose a home energy management system that employs load shifting strategy of demand side management to optimize the energy consumption patterns of a smart home. It aims to manage the load demand in an efficient way to minimize electricity cost and peak to average ratio while maintaining user comfort through coordination among home appliances. In order to meet the load demand of electricity consumers, we schedule the load in day-ahead and real-time basis. We propose a fitness criterion for proposed hybrid technique, which helps in balancing the load during ON-peak and OFF-peak hours. Moreover, for real-time rescheduling, we present the concept of coordination among home appliances. This helps the scheduler to optimally decide the ON/OFF status of appliances in order to reduce the waiting time of appliance. For this purpose, we formulate our real-time rescheduling problem as knapsack problem and solve it through dynamic programming. This paper also evaluates the behavior of the proposed technique for three pricing schemes including: time of use, real-time pricing, and critical peak pricing. Simulation results illustrate the significance of the proposed optimization technique with 95% confidence interval.

Integrated Smart Plug Design

Smart plug technology currently for user providing one plug module that is able to monitor and control the state of electrical appliance. The addition of plug number gives some deficiencies such as from cost point of view. By looking at the disadvantage made the tool which is able to monitor and control electrical appliance so that smart plug more than one integrated plug module. The manufacture of plug modules includes system design, sensor type selection in module, data delivery process, comparison of measurement module with measuring instrument and system test. From the results of the design is known that the module can perform data transmission, display the monitoring page and do the control and obtained percent accuracy of current readings obtained between 91.50% to 99.61% and the percent accuracy of the voltage readings obtained are ranged between 98.95% to 99.90%.

SMART INTERNET CONNECTED MOBILE PHONE REMOTE FOR MONITORING AND CONTROLLING OF HOUSE AND HOUSEHOLD APPLIANCES

Thinking about the ON/OFF state of electrical appliances, gas regulator and worrying about the safety of costly things in home are common to everyone. Carelessness or failing to off the appliances sometimes may cause minor or major accidents in home. The modern technologies available today will gives lot of solutions to overcome this problem. This paper gives details about a device built with sensors and Internet of Things (IoT), ZigBee wireless technology and a mobile phone application for monitoring and controlling. IoT means, things that are connected to internet and capable of accessing from anywhere. The device monitors the house with the help of sensors connected to it and updates information to the owner’s mobile phone through internet connection available in the house. The same way owner can control the home appliances and know its status from the mobile application. This device will reduce the burden of the owners, by keeping them aware of their home anywhere anytime. This device can also be useful for elderly and physically challenged people to control the appliances from mobile phone which is acting as a remote control in this device.

Unsupervised Residential Power Usage Monitoring Using a Wireless Sensor Network

Appliance-level power usage monitoring may help conserve electricity in homes. Several existing systems achieve this goal by exploiting appliances’ power usage signatures identified in labor-intensive in situ training processes. Recent work shows that autonomous power usage monitoring can be achieved by supplementing a smart meter with distributed sensors that detect the working states of appliances. However, sensors must be carefully installed for each appliance, resulting in a high installation cost. This article presents Supero —the first ad hoc sensor system that can monitor appliance power usage without supervised training. By exploiting multisensor fusion and unsupervised machine learning algorithms, Supero can classify the appliance events of interest and autonomously associate measured power usage with the respective appliances. Our extensive evaluation in five real homes shows that Supero can estimate the energy consumption with errors less than 7.5%. Moreover, nonprofessional users can quickly deploy Supero with considerable flexibility.

Load Signature Generator for Appliance State Sensing and Energy Disaggregation

Appliance state sensing is a load monitoring method that requires the ON/OFF states and global consumption measurements of appliances in order to achieve energy disaggregation. Previously proposed sensor networks employed uncalibrated, overrated, and costly wireless modules to collect appliance states. In contrast, we present a simple communication scheme, in which data are transmitted through the powerline to a main meter. For this purpose, we designed a smart sensor, the circuitry of which operates as a load signature generator. It generates fixed-amplitude and short-duration rectangular current pulses that encode information about the status of an appliance. For evaluation, we tested four sensors in a small electrical model and performed a numerical simulation using raw current waveforms contained in the reference energy disaggregation data set. The performance of the applied signal processing algorithms shows a symbol error rate of less than 1% when pulse position modulation with amplitudes of 2 A or more is used.

Design and Implementation of a Smart Home System Using Multisensor Data Fusion Technology.

This paper aims to develop a multisensor data fusion technology-based smart home system by integrating wearable intelligent technology, artificial intelligence, and sensor fusion technology. We have developed the following three systems to create an intelligent smart home environment: (1) a wearable motion sensing device to be placed on residents’ wrists and its corresponding 3D gesture recognition algorithm to implement a convenient automated household appliance control system; (2) a wearable motion sensing device mounted on a resident’s feet and its indoor positioning algorithm to realize an effective indoor pedestrian navigation system for smart energy management; (3) a multisensor circuit module and an intelligent fire detection and alarm algorithm to realize a home safety and fire detection system. In addition, an intelligent monitoring interface is developed to provide in real-time information about the smart home system, such as environmental temperatures, CO concentrations, communicative environmental alarms, household appliance status, human motion signals, and the results of gesture recognition and indoor positioning. Furthermore, an experimental testbed for validating the effectiveness and feasibility of the smart home system was built and verified experimentally. The results showed that the 3D gesture recognition algorithm could achieve recognition rates for automated household appliance control of 92.0%, 94.8%, 95.3%, and 87.7% by the 2-fold cross-validation, 5-fold cross-validation, 10-fold cross-validation, and leave-one-subject-out cross-validation strategies. For indoor positioning and smart energy management, the distance accuracy and positioning accuracy were around 0.22% and 3.36% of the total traveled distance in the indoor environment. For home safety and fire detection, the classification rate achieved 98.81% accuracy for determining the conditions of the indoor living environment.

GSM Module in Remote Electrical Loads Control

Electrical appliances power consumption tends to grow in proportion to the increase in the number of large-sized electric home appliances.These Projects describes the technology associated with the Remote Control of Electrical Loads Using GGSM Module. Using GSM networks, a control system has been projected that will act as an embedded system which can control appliances and other devices locally using built-in input and output peripherals. Also the system allow the user to effectively control house or office appliances and equipment via the mobile phone set by sending commands in the form of SMS messages and receiving the appliances status. The main conception behind this project is receiving a coded SMS to trigger or switch home electrical appliances through communication between GSM module and a microcontroller switching circuit.

복합 센서 데이터 처리 알고리즘을 이용한 비접촉 가전 기기 식별 알고리즘 연구

본 연구는 가정 내에서 사용하는 가전 기기의 사용 에너지를 효율적으로 관리하기 위한 비접촉 가전 기기 식별 기법을 제시한다. 제안하는 기법은 총 전력 사용량 정보를 이용한 기존의 가전 기기 식별 기법을 개선하기 위해서 복합 센서 정보를 종합적으로 활용한다. 이를 위해서 기기 상태와 측정된 센서 값 간의 영향도를 그래프 형태로 정의한다. 기기 상태에 영향을 미치는 복합 센서를 표현하는 영향도 그래프를 통해 기기 식별 예측 결과를 계산하기 위해 총 전력 사용량 기반 예측값과 센서 데이터 처리 알고리즘 예측값의 가중치 합을 사용한다. 시뮬레이션 실험을 통한 성능 분석으로 기존 비접촉 가전 기기 식별 기법의 기기 식별 정확도와 비교한다. In this study, we present a home appliance load identification algorithm. The algorithm utilizes complex sensory data in order to improve the existing NIALM using total power usage information. We define the influence graph between the appliance status and the measured sensor data. The device identification prediction result is calculated as the weighted sum of the predicted value of the sensor data processing algorithm and the predicted value based on the total power usage. We evaluate proposed algorithm to compare appliance identification accuracy with the existing NIALM algorithm.

One size does not fit all: Understanding user preferences for building automation systems

In recent years, technological advances have substantially extended the capabilities of automation systems in buildings. Despite the achieved advances, automation systems have not been widely adopted by building occupants. This paper presents our investigations on automation preferences of occupants for the control of lighting systems and appliances in residential buildings. A survey was carried out to determine how preferences for level of automation vary by contexts as well as individuals’ personalities and demographic characteristics. The contexts investigated in this study include rescheduling an energy consuming activity, activity-based appliance state control, and lighting control. The collected data from 250 respondents were analyzed using Generalized Linear Mixed Models. Our findings demonstrate that in all context no automation is the least preferred option. For rescheduling an energy consuming activity, an automation level with higher user participation is more preferred. For activity-based appliance state control and lighting control, levels of automation with lower user participation are more preferred. Our findings also indicate that income and education levels and also personality traits of agreeableness, neuroticism and openness to experience affect the preference of particular automation levels over the others. Findings from this study can be used in designing user-centered automation systems that lead to potentially more satisfying operation and hence, could enhance automation acceptability.

Dynamic time warping based non-intrusive load transient identification

Non-intrusive load monitoring (NILM) is a novel and cost-effective technology for monitoring load electricity energy consumption details. In the event-based NILM, transient power waveform (TPW) time-series can be used as signatures to identify the transients of the electrical appliances in the aggregated load, and then to determine their operating states, estimate their power demand and cumulative energy consumption. In this paper, for load transient identification, the dynamic time warping (DTW) algorithm is adopted for the first time to measure the similarity between the variable-length raw TPW sample and template time-series. Accordingly, a nearest neighbor transient identification method is proposed to identify the appliance creating the TPW sample time-series, in which the DTW-based integrated distance is used to measure the similarity of TPW signatures. Three schemes to calculate the integrated distance are designed, combining multiple types of TPW signatures. Comparison tests with existing methods are conducted using public datasets. The comparison test results indicate that the proposed load transient identification method cannot only improve the accuracy of load transient identification, but also is easy to implement at a reasonable cost. Ultimately, the proposed method is implemented in an embedded system. The field test results show that it can identify the operating states of electrical appliances with high accuracy.

A comprehensive embedded solution for data acquisition and communication using FPGA

Digital controllers in real time applications require a reliable system for acquisition of data for effective processing. This paper focusses on the design and development of a comprehensive embedded solution for data acquisition and communication using field programmable gate array (FPGA). In the proposed solution, an embedded platform is developed which acquires the data, monitors and provides essential communication between the devices connected via Ethernet in a network. The system utilizes server/client architecture mode of communication; control signals for the appliances connected to the client are controlled by the server and the status of appliances are displayed at server end for online monitoring. The proposed embedded solution works without a dedicated personal computer. The versatility and efficacy of the proposed platform is tested experimentally by employing it in a prototype of laboratory built micro-grid.

The Design and Implementation of a Low Cost and High Security Smart Home System Based on Wi-Fi and SSL Technologies

With the development of Internet of Things (IoT) and the popularity of intelligent mobile terminals, smart home system has come into people’s vision. However, due to the high cost, complex installation and inconvenience, as well as network security issues, smart home system has not been popularized. In this paper, combined with Wi-Fi technology, Android system, cloud server and SSL security protocol, a new set of smart home system is designed, with low cost, easy operation, high security and stability. The system consists of Wi-Fi smart node (WSN), Android client and cloud server. In order to reduce system cost and complexity of the installation, each Wi-Fi transceiver, appliance control logic and data conversion in the WSN is setup by a single chip. In addition, all the data of the WSN can be uploaded to the server through the home router, without having to transit through the gateway. All the appliance status information and environmental information are preserved in the cloud server. Furthermore, to ensure the security of information, the Secure Sockets Layer (SSL) protocol is used in the WSN communication with the server. What’s more, to improve the comfort and simplify the operation, Android client is designed with room pattern to control home appliances more realistic, and more convenient.

Performance Evaluation of the ZIP Model-Phaselet Frame Approach for Identifying Appliances in Residential Loads

This paper presents the analysis and development of a new approach to monitor and update the on–off status of appliances in residential loads (RSLs). The proposed approach is structured to employ power meter readings $P$ to determine the values for the magnitude $\vert \bar{S}\vert $ and phase $\theta$ of the apparent power. The value of $\vert \bar{S}\vert $ , associated with a value of $P$ , is determined using Newton iterations, where a value of $\theta$ is calculated using six phaselet frames during each iteration. Once the iterations converge, the values of $P$ and $\theta$ are used to construct the ZIP model (polynomial model) for the RSL, from which $P$ is provided. The constructed ZIP model provides the values for the constants $K_{pf}$ and $K_{qf}$ that relate the change in frequency to the active and reactive power demands of the modeled load. The obtained values of $K_{pf}$ and $K_{qf}$ are compared to standardized values that are defined for each appliance in an RSL. The ZIP model-phaselet frame approach is implemented as an algorithm for monitoring the on–off status of appliances in RSLs. The algorithm for the proposed approach is developed without a need to collect data for training. Test results show simple implementation, good accuracy, and insensitivity to variations in energy demands.

A Distributed and Scalable Approach to Semi-Intrusive Load Monitoring

Non-intrusive appliance load monitoring (NIALM) helps identify major energy guzzlers in a building without introducing extra metering cost. It motivates users to take proper actions for energy saving and greatly facilitates demand response (DR) programs. Nevertheless, NIALM of large-scale appliances is still an open challenge. To pursue a scalable solution to energy monitoring for contemporary large-scale appliance groups, we propose a distributed metering platform and use parallel optimization for semi-intrusive appliance load monitoring (SIALM). Based on a simple power model, a sparse switching event recovering (SSER) model is established to recover appliance states from their aggregated load data. Furthermore, the sufficient conditions for unambiguous state recovery of multiple appliances are presented. By considering these conditions as well as the electrical network topology constraint, a minimum number of meters are obtained to correctly recover the energy consumption of individual appliances. We evaluate the performance of both SIALM and NIALM with real-world trace data and synthetic data. The results demonstrate that with the help of a small number of meters, the SIALM approach significantly improves the accuracy of energy disaggregation for large-scale appliances.

Control and Communication Protocols Based on Packetized Direct Load Control in Smart Building Microgrids

Recent communication, computation, and technology advances coupled with climate change concerns have transformed the near future prospects of electricity transmission, and, more notably, distribution systems and microgrids. Distributed resources (wind and solar generation, combined heat and power) and flexible loads (storage, computing, EV, HVAC) make it imperative to increase investment and improve operational efficiency. Commercial and residential buildings, being the largest energy consumption group among flexible loads in microgrids, have the largest potential and flexibility to provide demand-side management. Recent advances in networked systems and the anticipated breakthroughs of the Internet of Things will enable significant advances in demand-response capabilities of intelligent load networks of power-consuming devices such as HVAC components, water heaters, EV charging stations, and many more. In this paper, a new operating framework, called packetized direct load control (PDLC), is proposed based on the notion of quantization of energy demand. This control protocol is built on top of two communication protocols that carry either complete or binary information regarding the operation status of appliances. We discuss the optimal demand-side operation for both protocols and analytically derive the performance differences between the protocols. We propose an optimal reservation strategy for traditional and renewable energy for the PDLC in both day-ahead and real-time markets. At the end of the paper, we discuss the fundamental tradeoff between achieving controllability and endowing consumer choice and flexibility.

Iterative learning for optimal residential load scheduling in smart grid

In this paper, as a fundamental problem in smart grid, the residential load scheduling is studied in a comprehensive way. The main contributions lie in threefold. First, three indices, i.e., the power consumption expense, the robustness of schedule subject to uncertain electricity price and the satisfaction of customer, are taken into full consideration. We propose to optimize simultaneously the three indices via convex optimization. Second, iterative learning is utilized to setting parameters in the objective function, and keeps a proper tradeoff between the consumption expense and the satisfaction index. Third, in order to fully characterize the operation states of appliances, both binary and continuous variables are used, which results in a hybrid mixed-integer quadratic optimization problem. The relaxation technique is utilized to tackle the hybrid optimization problem. Theoretical analysis of the performance gap based on the proposed approach is provided as well. The performance of the proposed approach is illustrated by simulations. The parameter settings reflect actual preference and consumption manner of the consumer. In addition, both peak-to-average ratio of power load and variation of power load are reduced.

MinNet: toward more intelligent smart home energy management systems with fewer sensors

The smart home technology has attracted considerable attention for decades. Nowadays, as the drastic increase of home energy consumption, efficient home energy management system HEMS has become a major building block. Aiming at building an easy-to-deploy intelligent HEMS, we design MinNet to i monitor the states of individual home appliances using the minimum number of power sensors and ii provide occupancy states of a house/room with inference intelligence. In detail, we use convenient plug-in power sensors to construct a wireless sensor network for data collection and establish an analytical framework based on the power model of appliances. By solving a carefully-designed optimisation problem, we find the minimum number of sensors to decode the states of appliances from their aggregated power and infer the occupancy states of the house/room. We implement MinNet in a house and validate its accuracy in appliance states monitoring and occupancy inference.

Implementation of Smart Homes and Industrial Automation System with Secure Communication over GSM

Home automation is method of controlling our house hold appliances, updating the status of lights, fans, motors and other appliances through any remote control device or mobile phones. Their ON/OFF status can be changed according to our desire. On the other hand, in present time, smart phones including android and iPhones are great inventions of technology. The awkwardness of hanging out along with a dedicated remote control device or texting an SMS for the automation purpose has always brought lake of interest in the user's mind towards using such systems. Therefore, in this activity we are introducing a smart home and industrial automation and surveillance system in which we control our appliances through an application installed in our smart phone which uses the available Global System for Mobile (GSM) features from any remote location within our planet, subject to the availability of GSM network. In other words the cumbersome of carrying dedicated separate remote control device and texting the SMS has been eliminated. For surveillance purpose, we used a Wireless Fidelity (Wi-Fi) camera, which uploads the picture or video streaming instantly in any website or sends it to the personal computer system. On the other hand the same purpose can be achieved by using any available software which could help communicating from any end station to PC. Each of these ideas is discussed in great detail in the paper. The proposed system is low in cost and we can reinstall it in any other location by only minor changes in its core. The proposed research work is very helpful for the layman and also to make life more comfortable and luxurious.

Clustering of Risk Behaviors and their Social Determinants among Primary School Learners in Beijing, China: A Cross-sectional Study.

Background:Studies in developed countries reveal that poor lifestyle choices triggering diseases typically cluster among children. However, there is insufficient evidence on the clustering of risk behaviors among children in developing countries. This study aimed to determine the clustering of risk behaviors and their social determinants among 4th-and 5th -grade learners in Beijing, China.Methods:The sample comprised of 967 learners from six primary schools enrolled migrant and resident learners by two-stage stratified cluster sampling. Prevalence denoted the risk behaviors and their clustering. A log-linear model was used to explore the clustering patterns. Ordinal logistic regression determined the influence of demographic characteristics, school environment, and family context on behavioral clustering.Results:The prevalence of none, one, two, and three or more risk factors was 61.2%, 20.0%, 10.8%, and 8.1% for infectious diseases and 46.0%, 30.6%, 15.4%, and 8.0% for chronic diseases, respectively. Some behaviors appeared dependent and were more likely to be observed together. The three most influential factors for infectious diseases were school type (odds ratio [OR] =4.47, 95% confidence interval [CI] 3.00–6.66), school located in an inner suburb (OR = 0.27, 95% CI 0.18–0.38), and gender (OR = 0.56, 95% CI 0.42–0.74). Regarding risk behaviors for chronic diseases, clustering was not associated with household registration status and number of appliances, but was significantly associated with school type (OR = 5.36, 95% CI 3.72–7.73), school located in an inner suburb (OR = 0.59, 95% CI 0.43–0.81), and gender (OR = 0.61, 95% CI 0.47–0.78). School environment variables were the most significant contributor to the number of risk behaviors.Conclusions:The characteristics of schools enrolling migrants and residents influenced the number of risk behaviors. Therefore, improved school conditions and integrated behavioral interventions are particularly recommended for health promotion.

A Study on the State of Home Appliances in terms of Information Accessibility for the Visually Impaired

현대사회에서 급속히 발전하는 IT기술의 발달과 터치스크린을 활용한 스마트기술은 시각에 의존한 정보제공방식으로 인하여 정보 불균형을 야기하는 문제점이 있다. 노약자 및 시각장애인은 가전제품 사용 시 필요한 정보에 접근하는 데서 발생하는 어려움을 겪고 있다. 따라서 본 연구에서는 가전제품 정보 접근성에 대한 실태 조사를 통하여, 가전제품의 조작 및 상태 인지 등에서 발생하는 문제점을 조사하고 가전제품의 정보 접근성에 대한 평가를 하고자 한다. 조사는 가전제품 관련 매장에 총 6군데를 방문하여 직접 관찰조사를 통해 2014년 8월 2일에서 22일 까지 진행되었다. 조사 대상은 세탁기, 밥솥, 전기인덕션, 전자레인지가 있었으며, 세탁기와 밥솥 중에서는 ‘사용자의 요구 사항’에 적합한 제품들이 관찰되었다. 전기인덕션과 전자레인지는 ‘사용자의 요구’에 맞는 제품을 찾기 어려운 것으로 나타났다. 터치 타입으로 된 패널들은 시각장애인이 조작하기에 어려운 것으로 나타났으며, 조작 시 필요한 정보 인지에 어려움이 있으므로 이는 시각장애인에게 부적절함을 알 수 있다. 노약자를 비롯한 다양한 사용자 배려한 조작방식과 두 개 이상의 감각을 이용하는 대안적 조절방식을 함께 제공하여 주택 가전제품의 정보접근성과 이용접근성을 함께 높일 필요가 있다.