Appliance Control Research Articles

Deep Sea Fisherman’s App using WWSN

In this study, we present a method for recognizing daily living activities using Doppler sensors with extended detection ranges, addressing key challenges in cost, accuracy, user convenience, and privacy preservation. We highlight the importance of accurate and affordable activity recognition for enabling advanced services in energy-saving home appliance control and other daily life applications. The proposed method leverages Doppler sensors' capabilities to detect dynamic objects and achieve precise recognition of a wide range of activities, including location-independent tasks like reading. Our evaluation includes optimizing recognition accuracy through logistic regression and assessing ensemble methods to enhance performance. Additionally, we explore the impact of sensor reduction strategies on recognition accuracy, demonstrating the potential of this approach to streamline sensor deployment while maintaining effectiveness. This research contributes to advancing sensor-based technologies for improving everyday life services, emphasizing practical solutions that prioritize cost-effectiveness and user experience

Hand Gesture Recognition for Home Automation using Machine Learning and ESP8266 Server

Automation is an evolving field providing immense aid in various fields. Types of automation include Artificial Intelligence, home automation, industrial automation, etc. Smart gesture based automation systems provides application in home automation which can support disabled and elderly persons. Home automation is the use and control of home appliances remotely or automatically. Every day the gap between humans and machines is being reduced. Recently introduced Metaverse and video game consoles like Play Stations gives us the insight of how the future of communication between human and computer would look like. Most of the electronic manufacturers are now focusing on hand gesture based automation. This proposed work uses the tool for the recognition and processing of hand gesture. Deep forest algorithm is used for image processing. At first, the image is captured by the camera and it is processed by OpenCV. This in turn controls the switching of home appliances. The hardware module consists of a camera, AVR AT Mega 328p microcontroller, relay module, power supply and bulbs for demonstration purpose. Supported by the pyFirmata protocol, the microcontroller and the appliances as connected seem less manner. The scope of application for this project is versatile, not limiting its functionality to a fixed application. This gesture based technology helps disabled and elderly people to use smart systems more effectively, reducing cost, man power and time to perform simple tasks for their comfort.

Automatic Home Controlling System for Paralyzed Patient using Eye Gestures

Abstract: The system revolutionizes the lives of paralyzed individuals by harnessing the power of eye-tracking technology for seamless control of home appliances. Utilizing OpenCV for robust and real-time eye tracking, the system enables patients to effortlessly interact with their surroundings by focusing on predefined patterns or commands. A user-friendly interface facilitates the establishment of a connection between eye movements and various household devices, including lights, fans, and entertainment systems. This innovative solution empowers individuals with limited mobility to regain independence, simplifying the management of daily routines and living spaces through intuitive gaze-based commands. By providing a novel avenue for communication and control, the system offers paralyzed patients a renewed sense of autonomy, convenience, and improved quality of life.

Model for Identification of Electrical Appliance and Determination of Patterns Using High-Resolution Wireless Sensor NETWORK for the Efficient Home Energy Consumption Based on Deep Learning

The growing demand for electricity and the constant increase in electricity rates have intensified the interest of residential and non-residential energy consumers to reduce their energy consumption. The introduction of non-conventional renewable energies (photovoltaic and wind, in the residential case) demands new proposals to obtain a home energy management system (HEMS), which allows reducing the use of electrical energy. This article incorporates artificial intelligence techniques to demand response, allowing control, switching, turning on and off of appliances, modifying and reducing consumption, and achieving improvements in the quality of life in the home. In addition, an architecture based on a smart socket and an artificial intelligence model that recognizes the consumption of electrical appliances in high resolution (sampling every 10 s) is proposed. The system uses the Wi-Fi communication protocol, ensuring that the smart sockets wirelessly provide the data obtained to the public cloud. The use of Deep Learning allows us to obtain a central control model of the home, which, when interconnected to the smart electrical distribution networks of companies, could generate a positive impact on the environmental effects and CO2 reduction.

Alveolar Bone and Gingival Changes in Mandibular Anterior Region Following Herbst Appliance Therapy: A Systematic Review and Meta-analysis.

To assess the alveolar bone changes and gingival recession following Herbst appliance therapy. Electronic databases such as PubMed, Ovid, Cochrane Library, Lilacs, Scopus, Web of Science, and Embase were searched until August 2022. Hand-searching of major orthodontic journals was performed to identify all peer-reviewed articles potentially relevant to the review. The quality of the selected studies was ranked using the revised Cochrane risk of bias tool for nonrandomized trials-Risk of Bias In Nonrandomized Studies (ROBINS) 1. Five relevant articles (all nonrandomized studies) were considered for qualitative analysis. The risk of bias was low for four studies and moderate for one. The reduction in the vertical alveolar bone height was 0.13 ± 0.07 mm, with the Herbst appliance. The mean difference in the loss of buccal cortical thickness between the Herbst appliance and untreated control group was 0.22 mm [95% confidence interval (CI) of -0.62-0.18]. Subsequent to Herbst appliance therapy, in the mandibular anterior region 0.1 ± 0.5 mm of gingival recession was observed. Herbst appliance treatment produces a negligible reduction in the buccal cortical thickness, vertical alveolar bone height, and gingival recession. Though the changes produced by the Herbst appliance were minimal, they are clinically important considering the young age of the patients warranting periodic periodontal assessment. Kumar MV, Kannan A, Kailasam V. Alveolar Bone and Gingival Changes in Mandibular Anterior Region Following Herbst Appliance Therapy: A Systematic Review and Meta-analysis. Int J Clin Pediatr Dent 2024;17(1):114-120.

Cost Focus versus Comfort Focus: Evidence from a Discrete Choice Experiment with Swiss Residential Electricity Customers

Based on a discrete choice experiment with 582 households in Switzerland, we find, that about 30% of the customers focus on price risks (cost focus) when they choose an electricity tariff, while 70% of the customers are more worried about volume risks (comfort focus). Customers with a cost focus, prefer contracts with low price risks and automatic load control, even when these contracts increased their volume risks and may lead to discomfort, while customers with a comfort focus are unlikely to choose a contract that exposes them to either price or volume risks. All customers prefer direct load control of individual appliances to capacity subscriptions or other demand response approaches which limit their total electricity demand. While customers with a cost focus likely accept direct load control even if this reduces their comfort, enrolling customers with a comfort focus will require further efforts and contracts avoiding comfort loss.

Third molar angulation and retromolar space after functional orthodontic treatment : Evaluation of panoramic radiographs after monoblock or Herbst appliance.

The aim of this respectively cohort study was to evaluate the lower second and third molars and canine angulations, retromolar space and occlusal relationships after functional orthodontic treatments with the monoblock or Herbst appliance using panoramic radiographs. Pre- and posttreatment cephalometric and panoramic radiographs of 133 patients (mean age 13.89 ± 1.14years) treated non-extraction with monoblock (n: 44), Herbst (n: 45) and fixed orthodontic appliances (control group; n: 44) were included to the study. Dental and skeletal measurements were performed on cephalometric radiographs. The angle between the third and second molars, and canines with the lower border of the mandible and the occlusal plane, gonial angle, the angle between the third and second molars and the retromolar space width were assessed on pre- and posttreatment panoramic radiographs. Paired and independent ttests were used for the statistical analysis of the data for intragroup and intergroup comparisons. Functional treatment with both the monoblock and the Herbst appliances resulted in improvement of skeletal classII relationships. Retromolar space significantly increased in the functional appliance groups compared to the control group (p ≤ 0.001), but improvement of the angulations of posterior teeth was significant only in the monoblock group (p ≤ 0.001). While both the Herbst and monoblock appliances led to an increase in retromolar space, monoblock treatment resulted in more favorable angulation of the third molars compared to the Herbst treatment.

Modeling of self-oscillating flexible circuits based on liquid crystal elastomers

Deformable and movable flexible circuits are characterized by simple construction, precise control, flexible and versatile morphology, and various functional forms, which can be used to build dynamic circuit systems, achieve the integration of drivers and controllers, and automated control of circuits, etc. Limited to conventional materials, challenges remain in designing novel self-oscillating flexible circuit. In this paper, a concept for a self-oscillating flexible circuit based on electrothermally responsive liquid crystal elastomers (LCEs) is presented, which is capable of generating periodic continuous oscillation under steady applied voltage. The governing equation of the self-oscillating LCE-based flexible circuit is formulated, and numerically calculated by fourth-order Runge-Kutta method with Matlab software. The numerical calculations reveal that the self-oscillating flexible circuit involves two motion patterns, i.e., static pattern and self-oscillation pattern. The self-oscillation arises from the coupling between the electrothermally driven deformation of the LCE film and its motion, and the electrothermal input compensates for the damping dissipation. Moreover, it is found that system parameters affect the self-oscillation of flexible circuit and that there are critical values of these parameters that trigger self-oscillation. Based on the self-oscillating flexible circuit, we conceptualized an automatic control device and a disturbance monitoring device, realizing automatic control of electrical appliances without human intervention and automatic monitoring of external disturbances. The proposed self-oscillating LCE-based flexible circuit features convenient operation, simple construction, flexibility, lightweight, and noiseless operation, rendering it suitable for constructing dynamic circuit systems, achieving actuator-controller integration, and facilitating circuit automation applications.

Artificial neural network-based home energy management system for smart homes

<p>Energy efficiency is widely recognized as one of the most significant and economical ways to lower greenhouse gas (GHG) emissions. The aims and goals are that smart meters can evaluate and communicate in-depth real-time electricity usage, enable remote real-time monitoring and management of power consumption, and provide consumers with real-time pricing and analyzed usage information. The house energy management controller decides which loads will be powered based on the real home energy demands and the predefined load priorities. Artificial intelligence (AI) is being used increasingly in control applications due to its great effectiveness and efficiency. As a result, in this work, the author designed, simulated, and optimized an artificial neural network-based model simulation framework that simulates a home with a variety of home appliances and optimizes the total energy consumption of the home realistically through intelligent control of home appliances. The MATLAB application was used to model and examine the performance of four common household appliances: the water heater (WH), washing machine (WM), air conditioner (AC), and refrigerator (RG). The result shows a considerable reduction and savings in energy consumption without a decrease in consumer comfort.<strong></strong></p>

A comprehensive dataset for home appliance control using ERP-based BCIs with the application of inter-subject transfer learning.

Brain-computer interfaces (BCIs) have a potential to revolutionize human-computer interaction by enabling direct links between the brain and computer systems. Recent studies are increasingly focusing on practical applications of BCIs-e.g., home appliance control just by thoughts. One of the non-invasive BCIs using electroencephalography (EEG) capitalizes on event-related potentials (ERPs) in response to target stimuli and have shown promise in controlling home appliance. In this paper, we present a comprehensive dataset of online ERP-based BCIs for controlling various home appliances in diverse stimulus presentation environments. We collected online BCI data from a total of 84 subjects among whom 60 subjects controlled three types of appliances (TV: 30, door lock: 15, and electric light: 15) with 4 functions per appliance, 14 subjects controlled a Bluetooth speaker with 6 functions via an LCD monitor, and 10 subjects controlled air conditioner with 4 functions via augmented reality (AR). Using the dataset, we aimed to address the issue of inter-subject variability in ERPs by employing the transfer learning in two different approaches. The first approach, "within-paradigm transfer learning," aimed to generalize the model within the same paradigm of stimulus presentation. The second approach, "cross-paradigm transfer learning," involved extending the model from a 4-class LCD environment to different paradigms. The results demonstrated that transfer learning can effectively enhance the generalizability of BCIs based on ERP across different subjects and environments.

Building a Secure IoT Platform for Smart Home Automation: A Comprehensive Integration

Abstract: The creation and use of a novel Internet ofThings (IoT) platform designed for smart home automation arepresented in this research study. The platform combines powerful hardware elements with cutting-edge software technologies. It makes use of Docker ptimization on, an Ubuntu-based Linux server, and essential utilities like Traefik, MySQL, Node-RED, Mosquitto, Adminer, and InfluxDB. The infrastructure is painstakingly built to provide scalable deployment, effective data management, and smooth communication. The core of the technique is the creation of a Linux server running Ubuntu. A flexible reverse proxy called Traefik ptimizat web traffic and makes sure that components communicate with one other effectively. Docker ptimization on is used for the modular deployment of services,such as the central orchestrator Node-RED, the lightweightMQTT broker services provided by Mosquitto, and MySQL for structured data storage. Time-series data processing and database administration are improved by the combination of Adminer and InfluxDB. The visual programming tool Node- RED acts as the central data flow orchestrator, allowing databases and devices to be connected with ease. Real-time datainterchange is ensured via MQTT implementation usingMosquitto, which is essential for Internet of Things applications.Network protocols, Docker best practices, and optional SSL/TLS implementation are just a few of the security features that provide a stable and secure environment. Security audits are planned on a regular basis to find and fix such weaknesses. Hardware for home automation control includes DHT11 sensors, 4-channel relay modules, and ESP32 development boards. Beyond simple automation, the platform includes functionalities for sensor data collecting, remote device administration, and intuitive appliance control via a Node-RED Dashboard. Applications include temperature, humidity, and air quality monitoring, as well as security and surveillance withbuilt-in cameras and motion sensors.

РОЛЬ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В БИЗНЕСЕ

Small businesses play a vital role in the fabric of any economy. The Small Business Administration recognizes their significant contributions to economic growth, job creation, innovation, and overall prosperity. These businesses, although small in scale and often privately owned, have significant value compared to larger corporations. The definition of a small business can vary from country to country and industry to industry, encompassing factors such as the number of employees, annual revenue, and assets. Although various AI technologies are used quite often in everyday life (72% of respondents use voice assistants, smart gadgets, or automatic control of home appliances), less than half of respondents (45%) have used AI in their work processes in the past year. The most popular tasks are creative ones, which usually take up a lot of employees' operational time. For example, instead of recording a meeting and then spending several hours transcribing it, speech recognition technologies are used to translate it into text. Communication with customers can be simplified with the help of smart voice assistants. In order to find analogues of your products, it is not necessary to physically go around all competitors, sometimes it is enough to upload a photo to the image recognition and analysis service. However, only 19% of entrepreneurs used the capabilities of chatbots in their work that can support a dialogue, or virtual assistants that make an action plan and write a scenario, 4% of entrepreneurs tried to work with a neural network that understands requests in Russian and English, can mix images, mix images and text, create different versions of images, and also redraw individual objects and areas in pictures. 78% of entrepreneurs who used artificial intelligence technologies in their work consider them useful for their activities. Among the main advantages, respondents noted the release of employee time for other tasks (56%), high speed of execution (50%) and money savings (35%).

In-depth investigations into symmetrical labyrinthine acoustic metamaterial with two micro-slit entries for low-frequency sound absorption.

Sound absorption below 1000 Hz has been extremely difficult through traditional barriers and absorbers, but it is required for noise control of appliances and machineries. Existing passive acoustic metamaterials attenuate low-frequency noise but with narrow bandwidths and bulky sizes. Hence, this paper proposes an acoustic metamaterial with enclosed symmetrical labyrinthine air channels and two micro-slits (configuration 1, identical slits; configuration 2, unequal length slits) at the end channels. Its theoretical model is established by acoustic impedance analysis using electro-acoustic analogy and validated numerically and experimentally. Sound absorption is found to happen as a result of impedance matching, Fabry-Perot-like labyrinthine resonances, and thermo-viscous losses in micro-slits. Parametric investigations reveal that increase in the number of channels, channel length, total height, and outer panel thickness shifts sound absorption peak to lower frequency but also decreases the magnitude and frequency range of absorption. Decreasing the channel width and slit width increases the sound absorption magnitude without changing absorption frequencies. Interestingly, unequal slit lengths perform better than equal slits by giving a lower frequency sound absorption with increased magnitude and frequency range, which is unlike that in existing labyrinthine metamaterials. Therefore, the proposed unequal slit metamaterial has enhanced low-frequency sound absorption and can be applied to appliances and machineries.

Adaptive Load Shedding as Part of Primary Frequency Response To Support Networked Microgrid Operations

Global changes in the deployment of distributed energy resources, control and communications technologies, business models, and regulatory policy are increasing the operational options for future distribution systems. One such option is the coordinated operation of distributed resources to form microgrids and networks of microgrids to support traditional bulk power systems during normal operations and critical end-use loads during outages. While individual standalone microgrids have been extensively studied and deployed, the coordinated operation of networked microgrids is operationally more challenging due to the dynamic boundaries and changing mix of generation resources. This paper presents a method of using a distributed control architecture to support primary frequency response in networked microgrids operations. The support of primary frequency response is accomplished using the Open Field Message Bus reference architecture and Grid Friendly Appliance controllers.

A COMPUTERIZED ENERGY MANAGEMENT SYSTEM FOR A SMART HOME

This work is devoted to the study of Smart Home systems based on the development of an energy optimization system for a smart home and based on various wireless communication protocols. The paper considers the construction of a home monitoring and control system based on the latest Bluetooth Low-Energy protocol using modern technologies. A device for monitoring and controlling electrical appliances, which is an element of this system, is proposed. The proposed architecture has advantages over other existing systems: reliability, performance, ease of deployment, and management. The system is flexible due to the possibility of selecting operating modes (automatic or manual) and changing various settings that affect the operation of the optimization algorithm. The paper presents examples of the system operation in different modes and at different values of the algorithm settings, consisting of a server deployed on a personal computer and two developed monitoring and control device prototypes. Keywords: smart home, energy consumption optimization, monitoring and control of electrical appliances, smart sockets, Bluetooth low energy.

MODEL RUMAH DIGITAL BERBASIS ARDUINO UNO MENGGUNAKAN MIKROKONTROLER ATMEGA 328P

The vulnerability of homeowners is a significant factor in various criminal activities, such as forgetting to lock doors or leaving the house with lights off. Therefore, it is necessary to design a digital home that allows homeowners to control their homes remotely. This research aims to build and enhance a smart home, which has been previously studied. Through this development, the smart home transforms into a digital home by adding several features. The features include Home Door Security, Home Temperature Monitoring, and Home Appliance Control via SMS. The digital home is expected to be beneficial in preventing crimes and addressing negligence-related incidents. By providing access codes to unlock doors, it helps prevent unauthorized entry, enhancing home security. Additionally, it addresses safety concerns related to negligence, such as electrical short circuits or gas leaks that may lead to fires. The digital home can provide immediate assistance by reacting to abnormal temperatures detected by sensors, activating fans to normalize the temperature. If the temperature remains above the specified limit, a danger alarm will sound, indicating an issue inside the house. Another function is the ability to control home appliances remotely via text messages (SMS) when the homeowner is away.

Evaluation Of Internet Of Things (Iot) For Monitoring And Control Of Home Electronic Appliances

This research aims to evaluate the effectiveness and reliability of Internet of Things (IoT) technologies in the context of monitoring and control of household electronic appliances. Rapid developments in the IoT domain have opened up new opportunities to integrate home appliances into a connected digital ecosystem, with the aim of improving user efficiency, convenience, and security.
 The methodology of this research includes the implementation of an IoT infrastructure consisting of sensors, actuators, and communication platforms, as well as the development of control applications via mobile devices. Selected household electronic appliances, such as lighting devices, air conditioners, and security systems, will be integrated into the IoT network to facilitate remote monitoring and control.
 During the evaluation, performance parameters such as response time, connection reliability, and energy consumption will be measured and analyzed. In addition, user experience in using the control application via mobile devices will also be evaluated through questionnaires and interviews.
 The results of this study are expected to provide in-depth insights into the potential and limitations of IoT implementation for monitoring and control of household electronic appliances. The implications of the results of this study can support the development of better solutions in creating a smart, efficient, and customizable home environment according to individual preferences and needs.

Scalable investigation of energy usage patterns and saving potential in hotel guestrooms: Focused on occupancy states and electrical installations

In hotel guestrooms, under the category of non-stationary-operated building, energy usage patterns can vary significantly depending on occupant behaviors and preferences, making it challenging to formulate feasible energy-saving strategies. To address the challenge, this study proposes a scalable approach to investigate energy usage patterns and saving potential in hotel guestrooms, in which endogenous parameters (occupancy states and electrical installations) are comprehensively considered. The data was collected over a year from three guestrooms of Hotel “I” in Hong Kong, including energy usage for different electrical installations, indoor temperature and humidity, and check-in or check-out information. The main findings can be summarized as follows. First, energy usage patterns revealed that the average 15-minute interval energy usage during the check-in state was 56.49 Wh, while during the check-out state, it was 44.03 Wh (77.94% compared to the check-in state). Second, the proposed energy-saving strategies can be applied to the case study room, leading to a reduction of 247.53 kWh, which corresponds to 13.79% of the current annual energy usage (1,794.55 kWh) in the case study room. The proposed scalable approach is expected to contribute to enabling occupant-centric appliance control strategies in hotel guestrooms, depending on occupancy states, which leads to cost savings and promises various benefits, such as enhanced guest services and promotional advantages, such as “Green Hotel”.

GOVERNANCE OF IOT DEVICES USING NODE-RED ORCHESTRATOR AND WEB-BASED DASHBOARD

High electricity bills are often caused by a lack of monitoring the use of electronic equipment in the household. One common problem is forgetting to turn off appliances that are not in use, which causes electricity to continue flowing and increases electricity bills. Currently, although there are several technologies that allow the control of appliances, their features are still limited, especially in lamps. This research focuses on developing Internet of Things (IoT) technology in the field of energy and control. One of the implementations is using a Raspberry Pi microcontroller to monitor the use of electrical energy in households. In order to make the use of IoT components more efficient and easier, a NODE-RED-based system is used which serves as a link between end users and IoT equipment. For monitoring IoT components, a web dashboard using the Laravel framework was also built. This allows users to view the components used and the activities that occur on their IoT equipment. High electricity bills are often caused by a lack of monitoring the use of electronic equipment in the household. One common problem is forgetting to turn off appliances that are not in use, which causes electricity to continue flowing and increases electricity bills. Currently, although there are several technologies that allow the control of appliances, their features are still limited, especially in lamps. This research focuses on developing Internet of Things (IoT) technology in the field of energy and control. One of the implementations is using a Raspberry Pi microcontroller to monitor the use of electrical energy in households. In order to make the use of IoT components more efficient and easier, a NODE-RED-based system is used which serves as a link between end users and IoT equipment. For monitoring IoT components, a web dashboard using the Laravel framework was also built. This allows users to view the components used and the activities that occur on their IoT equipment.

Artificial Intelligence Based Chatbot for Appliance Control

Now a days, numerous uses of artificial intelligence are found in the healthcare industry. Building advanced devices that can detect diseases and identify cancer cells uses AI applications. In order to ensure early diagnosis, artificial intelligence can assist in analyzing chronic illnesses with lab and other medical data. In this study, an IoT based home management and monitoring system with cheap cost and flexibility is presented. Using the Facebook Messenger app, users may access and remotely operate gadgets and appliances using smart phones. In contrast to prior systems, the proposed system provides a communication protocol to monitor and control the home appliences with the Messenger app in smart phones. The intelligent networking of common place devices like smart phones, Internet TVs, sensors, and actuators to the Internet is known as the Internet of Things (IoTs). New forms of communication between objects and humans as well as between things and other things are made possible by this. Now that everyone, from anywhere, can have connectivity for anything, In this project, the Facebook Messenger and the ESP8266-12E NodeMCU are used to operate electrical home appliances. Chatfuel is the tool used to build Facebook AI chatbots. IFTTT and Adafruit IO are also used by the project for back-end assistance.