Smart Home Automation System Research Articles

Papermaking-inspired sustainable triboelectric sensors for intelligent detecting system

Digitalization not only drives the intelligent transformation of industries while fostering cultural diversity and innovation. Cutting-edge triboelectric sensing technology inspired by traditional Chinese papermaking fabricates a bamboo paper-based triboelectric nanogenerator (BP-TENG). The addition of high-purity bacterial cellulose improves the structural integrity of the resulting paper. The proposed BP-TENG exhibits excellent electrical performance, generating an output voltage of 88 V and a maximum output power of 0.9 mW at a low-frequency motion of 2 Hz. Moreover, the BP-TENG is combined with machine learning algorithms to build a multi-scene intelligent detecting system, including real-time handwriting-to-speech conversion, personalized jump prediction and smart home automation systems. The machine learning algorithm can achieve a recognition accuracy of up to 99.8 %. This multi-scene intelligent detecting system boasts superior accuracy, environmental sustainability and affordability, ideal for communication security, sports health monitoring and smart building applications.

A secured deep learning based smart home automation system

With the expansion of modern technologies and the Internet of Things (IoT), the concept of smart homes has gained tremendous popularity with a view to making people’s lives easier by ensuring a secured environment. Several home automation systems have been developed to report suspicious activities by capturing the movements of residents. However, these systems are associated with challenges such as weak security, lack of interoperability and integration with IoT devices, timely reporting of suspicious movements, etc. Therefore, the given paper proposes a novel smart home automation framework for controlling home appliances by integrating with sensors, IoT devices, and microcontrollers, which would in turn monitor the movements and send notifications about suspicious movements on the resident’s smartphone. The proposed framework makes use of convolutional neural networks (CNNs) for motion detection and classification based on pre-processing of images. The images related to the movements of residents are captured by a spy camera installed in the system. It helps in identification of outsiders based on differentiation of motion patterns. The performance of the framework is compared with existing deep learning models used in recent studies based on evaluation metrics such as accuracy (%), precision (%), recall (%), and f-1 measure (%). The results show that the proposed framework attains the highest accuracy (98.67%), thereby surpassing the existing deep learning models used in smart home automation systems.

Adaptive multi-task ensemble framework for smart home automation

Smart home technology has evolved rapidly with an emphasis on indoor environmental control. It aims to automate the control of the indoor environment through sensors, regulators, and other technologies in order to improve comfort, energy saving, emission reduction, safety, and intelligence. However, there is still a research gap between existing research and real-world applications. Most studies focus on modeling individual regulators, neglecting the cooperation between elements that influence the experience of the occupants. This leads to several cooperation issues like inconsistent and overlapping control. In addition, few studies have focused on the performance degradation of the entire system over the life cycle. To bridge the above missing gap, this paper proposes an adaptive multi-task framework that combines graph neural networks, multi-task learning, and incremental learning to achieve better cooperation and synergy among multiple regulators. The framework has been successfully tested on a wide range of smart home automation systems, achieving a 5–15 % improvement in performance for each individual regulator. Meanwhile, the proposed framework also demonstrates significant advantages against performance degradation over the life cycle. It provides a feasible, user-friendly, consumer-oriented framework for indoor environment automation that assists the entire system to improve the user experience.

Prototype, method, and experiment for evaluating usability of smart home user interfaces

Despite the widespread adoption of smart devices and home automation systems, users still face usability challenges. Additionally, evaluating the usability of smart home systems is not straightforward. Our paper focuses on building a Smart Home Prototype, selecting, and evaluating software User Interfaces (UI). We have chosen the smart home heating system as the basis, but the principles are applicable to other applications. To discuss smart home UIs, it is necessary to understand the components, implementation scenarios, configuration, and operation of smart home systems. Therefore, we devote considerable attention to these topics in the paper. Our smart home system utilizes a Raspberry Pi computer, temperature sensors, servo drives, an Android-based smartphone, and other necessary hardware. We installed and configured open-source software and third-party services on the experimental setup. We provided a brief description of each selected software. We used the Home Assistant operating system, its mobile application, voice assistant Alice, and Telegram chatbot. In our study, we described a methodology for evaluating user interfaces in smart homes and conducted an experiment to assess their usability. The experiment results indicated which interface was more user-friendly and identified the drawbacks of each. In conclusion, we discuss UI features that can improve usability and available options for building a smart home based on capabilities.

Design and Implementation of an IOT-based Smart Home Automation System in Real World Scenario

INTRODUCTION: Automation developments have significantly increased general convenience in modern technology. Our study focuses on developing and deploying an Internet of Things (IoT)–enabled smart home automation system that maximizes energy efficiency and improves convenience in residential settings. Our technology provides homes with an intelligent environment by smoothly combining several sensors, actuators, and communication protocols. We explore the challenges of creating a reliable and useful smart home systemthat works well in everyday situations. We investigate the difficulties, architectural issues, communication protocols, and security features specific to these systems.OBJECTIVES: This project aims to use a database server and Wi-Fi module to develop an effective and reasonably priced smart home automation system. It improves accessibility and convenience by enabling smartphone voice control of household appliances.METHODS: This project was developed using various implementation techniques, including wireless home automation via GSM technology, speech recognition-based systems, Blynk, and the Internet of Things. These techniques added up to a reliable and effective smart home system.RESULTS: Although it improved user routines, the IoT-based smart home system had latency problems. Interoperability issues are still present. Improvements were guided by user input. Using Blynk, our software manages loads remotely. CONCLUSION: A home automation system that is inexpensive and locally supplied can effectively operate household appliances. It is adaptable, scalable, and a component of future smart homes. IoT applications in real life revolutionize convenience and efficiency in living environments.

Smart Home Automation System Using IOT

The concept of a "smart home" is rapidly gaining popularity among homeowners worldwide, and it's all thanks to the integration of WiFi connectivity. Smart home automation systems driven by WiFi offer exciting new possibilities for enhancing our living spaces, from increased comfort and convenience to greater energy efficiency and sustainability. By leveraging the power of WiFi, smart home automation systems enable us to remotely monitor and manage various aspects of our homes using smartphones, tablets, or other internet-enabled devices. Plus, these systems are designed to seamlessly communicate and integrate across different manufacturers and platforms, making it easier than ever to customize your living space to suit your needs. But the benefits of smart home automation systems go beyond mere convenience. They also have the potential to significantly reduce our energy consumption, minimize waste, and contribute to a more sustainable future. At the same time, integrated sensors, cameras, and motion detectors can enhance our home security and safety, providing peace of mind and mitigating risks associated with burglary, fire, or other hazards. Ofcourse, there are some challenges and considerations to keep in mind when it comes to WiFi-enabled smart home automation systems. Privacy and data security are top concerns, and interoperability and compatibility issues must be addressed to ensure that these systems remain flexible and adaptable to the evolving needs and preferences of homeowners. Additionally, user-friendly interfaces and intuitive design principles are essential for ensuring a positive and enjoyable experience. In this research paper, we aim to explore the transformative potential of WiFi-enabled smart home automation systems and provide constructive insights into how we can overcome the challenges and considerations associated with this technology. By shedding light on the opportunities, challenges, and best practices associated with these systems, we hope to empower homeowners, policymakers, and industry stakeholders alike to make informed decisions that enhance the quality of life while safeguarding privacy, security, and sustainability.

SMART HOME AUTOMATION SYSTEM USING IOT

The concept of a "smart home" is rapidly gaining popularity among homeowners worldwide, and it's all thanks to the integration of WiFi connectivity. Smart home automation systems driven by WiFi offer exciting new possibilities for enhancing our living spaces, from increased comfort and convenience to greater energy efficiency and sustainability. By leveraging the power of WiFi, smart home automation systems enable us to remotely monitor and manage various aspects of our homes using smartphones, tablets, or other internet-enabled devices. Plus, these systems are designed to seamlessly communicate and integrate across different manufacturers and platforms, making it easier than ever to customize your living space to suit your needs. But the benefits of smart home automation systems go beyond mere convenience. They also have the potential to significantly reduce our energy consumption, minimize waste, and contribute to a more sustainable future. At the same time, integrated sensors, cameras, and motion detectors can enhance our home security and safety, providing peace of mind and mitigating risks associated with burglary, fire, or other hazards. Ofcourse, there are some challenges and considerations to keep in mind when it comes to WiFi-enabled smart home automation systems. Privacy and data security are top concerns, and interoperability and compatibility issues must be addressed to ensure that these systems remain flexible and adaptable to the evolving needs and preferences of homeowners. Additionally, user-friendly interfaces and intuitive design principles are essential for ensuring a positive and enjoyable experience. In this research paper, we aim to explore the transformative potential of WiFi-enabled smart home automation systems and provide constructive insights into how we can overcome the challenges and considerations associated with this technology. By shedding light on the opportunities, challenges, and best practices associated with these systems, we hope to empower homeowners, policymakers, and industry stakeholders alike to make informed decisions that enhance the quality of life while safeguarding privacy, security, and sustainability.

Integration of Smart Home and Building Automation Systems in Virtual Reality and Robotics-Based Technological Environment for Neurorehabilitation: A Pilot Study Protocol.

Technological innovation has revolutionized healthcare, particularly in neurological rehabilitation, where it has been used to address chronic conditions. Smart home and building automation (SH&BA) technologies offer promising solutions for managing chronic disabilities associated with such conditions. This single group, pre-post longitudinal pilot study, part of the H2020 HosmartAI project, aims to explore the integration of smart home technologies into neurorehabilitation. Eighty subjects will be enrolled from IRCCS San Camillo Hospital (Venice, Italy) and will receive rehabilitation treatment through virtual reality (VR) and robotics devices for 15 h per day, 5 days a week for 3 weeks in the HosmartAI Room (HR), equipped with SH&BA devices measuring the environment. The study seeks to optimize patient outcomes and refine rehabilitation practices. Findings will be disseminated through peer-reviewed publications and scientific meetings, contributing to advancements in neurological rehabilitation and guiding future research.

NIKKY THE HUMANOID ROBOT FOR HEALTHY AND SAFETY LIVING

As the global population ages, the demand for effective elderly care solutions has become increasingly urgent. With advancements in technology, there arises an opportunity to revolutionize the way we approach elderly care, moving beyond traditional models towards more innovative and integrated approaches. This project introduces an integrated smart home automation system designed to enhance the well-being and independence of seniors while providing invaluable support to caregivers. Leveraging cutting-edge technologies such as AI integration, IoT devices, and voice recognition, the system offers a seamless and intuitive user experience. Features include automated task management, real-time environmental monitoring, medication management, and emergency response capabilities. By streamlining daily routines, promoting social engagement, and ensuring safety, the system aims to improve the overall quality of life for seniors while alleviating stress and burden for caregivers. Additionally, this project explores the potential of humanoid robot technology, exemplified by robot Nikky, to further augment elderly care through human-like interactions and assistance. This integrated approach not only addresses physical needs but also focuses on cognitive stimulation and emotional well-being, fostering a sense of companionship and purpose for seniors. Through these efforts, this project seeks to address the evolving needs of aging populations and contribute to the advancement of technology-driven solutions in elderly care and support services. Key Words: Home automation, Robotics, Smart and healthy living, Humanoid Robot for personal interaction

Wireless Home Security Using IOT

Abstract: We are living in the fourth industrial revolution. Our life is becoming more comfortable and smarter with the help of rapid upgrade of technology. Internet of things (IOT) is playing a massive role in this. One of the major sides of IOT is a smart Electrical Appliances. As we are in the era of never-ending growth of the internet and its application, smart home system or home automation system is highly increasing to provide comfort in life and improving the quality of life. In this project, we present an IOT based low cost smart electrical equipment automation system. This system is based on a web portal which controlled by an ESP32 WI-FI module. Also, a custom-made private web server is developed for maintaining the current states of electrical devices appliances.

Automated Domesticity: Exploring the Realm of Home Automation Systems

This research paper presents the development and implementation of a comprehensive smart home automation system comprising a smart switchboard, smart smoke, flame, and gas detector, and a smart door lock system. Leveraging innovative technologies such as voice control, sensor networks, and Bluetooth Low Energy connectivity, the system offers users enhanced convenience, safety, and energy efficiency within residential environments. The smart switchboard enables intuitive voice-controlled operation alongside traditional manual control options, while the smart smoke, flame, and gas detector provide real-time monitoring and alerting capabilities. Additionally, the smart door lock system ensures secure access control through voice password authentication and manual lock and key options. Through this integration, our research demonstrates the transformative potential of smart home automation in revolutionizing household management and enhancing quality of life

An Integrated Gesture Framework of Smart Entry Based on Arduino and Random Forest Classifier

Gesture-based systems have emerged as a prominent breakthrough in the field of smart access control, effectively integrating security measures with user comfort. This study presents a novel gesture detection framework for smart entry systems that combines the computational capabilities of a Random Forest Classifier with the practicality of Arduino-based hardware. Central to methodology is the utilization of MediaPipe, an advanced computer vision library, to extract hand motion landmarks from live video streams. The selected landmarks function as a comprehensive dataset for training a Random Forest Classifier, which has been specifically chosen due to its high level of accuracy and efficiency in managing intricate classification jobs. The model exhibits outstanding competence in the categorization of gestures in real-time, attaining high levels of accuracy that are crucial for ensuring dependable entrance control. The Arduino microcontroller plays a vital role in the execution of the entry mechanism as it serves as the intermediary between the gesture detection software and the tangible entry control hardware. The incorporation of gesture recognition technology facilitates a cohesive and prompt user experience, wherein identified motions are directly converted into input commands. The system's practical use is demonstrated through a series of detailed tests, which highlight its dependability and efficiency across diverse climatic circumstances. The findings underscore the system's capacity as a flexible and safe solution for contactless access in many environments, including both private homes and highly protected establishments. Furthermore, the study makes a substantial contribution to the larger domain of human-computer interaction by showcasing the practicality of advanced gesture detection systems in many everyday contexts. The suggested framework presents a novel approach to smart entry systems and also paves the way for further investigation in the domains of smart home automation and interactive systems. In these areas, gesture-based interfaces have the potential to deliver user experiences that are both intuitive and efficient.

Development and implementation of a smart home automation system in the context of the Ukrainian housing sector: Challenges and prospects

Due to the rapid development of technology and the growing interest in the concept of “smart home”, the relevance of the study is to identify obstacles and opportunities, contributing to the effective implementation of these technologies in modern life. The purpose of this study is to analyse the modern state and determine the possibilities of developing and implementing smart home automation systems in the Ukrainian residential sector to increase the level of comfort, safety, and energy efficiency. The methods used include the analytical method, classification, functional method, statistical method, synthesis, etc. The results of the study reveal the profound impact of technology on the efficiency and security of a smart home. The modern state of smart home automation systems in the Ukrainian residential sector was analysed. Modern cybersecurity methods for protecting against potential threats were considered. Electronic keys, including Face Identification, fingerprint and voice recognition technologies, are being implemented to provide access and increase security in the smart home. The study reveals various methods that are used in different countries to implement smart homes, presenting various examples of development and features of their implementation. As a result, key technical and financial challenges are identified that call into question the effectiveness of implementing such systems. In addition, the possibilities of optimising these systems were considered based on market features and infrastructure constraints. According to the analysis, specific recommendations were developed for creating affordable and effective solutions for Ukrainian consumers. Based on these recommendations, it can be concluded that, despite the existing difficulties, the introduction of smart home systems in Ukraine has potential and prospects. However, to achieve full success, it is important to overcome technological challenges and consider the financial capabilities of the population. The study made a significant contribution to understanding the factors influencing the successful implementation of modern technologies in the residential sector of Ukraine, contributing to the practical development of science and providing concrete conclusions for the possibilities of implementing smart home automation systems

SMART HOME AUTOMATION SYSTEM FOR ENERGY CONSUMPTION USING TENSORFLOW-BASED DEEP ENSEMBLE LEARNING

Over the past decades, the evolution of new wireless technology has led to increased attention toward Smart Home Automation Systems (SHAS). In the smart home, numerous smart devices are interconnected with the proliferation of the Internet of Things (IoT) technology to provide users with a more comfortable lifestyle. Prior research on the smart home system has enacted machine learning and deep learning techniques to forecast the consecutive activities in the smart home. This research paper aims to enhance the future decision-making of energy consumption with the assistance of environmental factors and home appliances by exploiting the Tensorflow-based deep ensemble learning technique. The enhancement of future decision-making in smart home automation systems primarily involves the classification of energy consumption levels from the knowledge of external environmental factors and energy consumption levels of home appliances through the phases of data preprocessing, feature selection, fuzzy logic-based data labeling, and finally, classification of energy consumption using TensorFlow based deep ensemble learning technique. The data obtained from the effective feature selection technique is subjected to labeling via the fuzzy logic system to classify the energy consumption of smart home appliances. Finally, this work classifies the level of energy consumption based on the labeled knowledge of smart home data using a tensorflow-based deep ensemble learning model. The experimental model implements the proposed deep ensemble learning model in the tensorflow framework, which improves the decision-making performance of energy utilization in the smart home system. Experimental results illustrate that the proposed deep ensemble learning model yields superior classification performance than the other baseline classifiers, such as Artificial Neural Network (ANN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM) on the smart home dataset.

Internet of Things (IoT) and Smart Home Automation: Enhancing Living Spaces

The Internet of Things (IoT) has emerged as a transformative technology with the potential to revolutionize various aspects of modern living, including the way we interact with our living spaces. This paper explores the integration of IoT into smart home automation systems and its implications for enhancing the functionality, efficiency, and convenience of living spaces. We discuss the challenges and opportunities associated with this technology, and present a comprehensive analysis of existing and proposed systems. Through an extensive review of the literature, we highlight the benefits and potential drawbacks of IoT-enabled smart homes. The findings of this research emphasize the need for robust security measures, interoperability standards, and user-centered design to fully realize the potential of IoT in shaping the future of living spaces

A Secure and Smart Home Automation System with Speech Recognition and Power Measurement Capabilities.

The advancement in the internet of things (IoT) technologies has made it possible to control and monitor electronic devices at home with just the touch of a button. This has made people lead much more comfortable lifestyles. Elderly people and those with disabilities have especially benefited from voice-assisted home automation systems that allow them to control their devices with simple voice commands. However, the widespread use of cloud-based services in these systems, such as those offered by Google and Amazon, has made them vulnerable to cyber-attacks. To ensure the proper functioning of these systems, a stable internet connection and a secure environment free from cyber-attacks are required. However, the quality of the internet is often low in developing countries, which makes it difficult to access the services these systems offer. Additionally, the lack of localization in voice assistants prevents people from using voice-assisted home automation systems in these countries. To address these challenges, this research proposes an offline home automation system. Since the internet and cloud services are not required for an offline system, it can perform its essential functions, while ensuring protection against cyber-attacks and can provide quick responses. It offers additional features, such as power usage tracking and the optimization of linked devices.

Development of an Android Based Home Automation System

As automation technology keeps advancing, the future of modern homes is continually changing from manual system into automatic ones that include remote control process. A Conventional means of accessing home electronic appliances is rigid and demands user presence to attend to different locations of such appliances before they can be used, this can be stressful for the elderly, the cripples, and provides limited ease of operation for everyone. The need for wireless communication function of the home appliances becomes very important in order to increase the flexibility of accessing them remotely by a user. Accessing and control of electronic devices and appliances used at home through a remote process is the main purpose for the development of a portable home automation system using app that is based on an android phone. ESP8266 microcontroller was interfaced to a servo motor that controls door movement and also to an AC bulb through a relay at the signal receiver end of the system. An MIT application inventor platform was used to build a mobile app on an android phone at the signal transmitter end of the system; this enables the transmission of on and off signals to the receiver end through Wi-Fi connection to access the connected loads (door and lamp). The hardware and software architecture of the developed home automation system was described in this paper. Implementation of a prototype of the designed system was carried out after which the system was tested on hardware as it yields expected results.

IoT-based smarthomes to increase home selling price

Smarthome is a system that has been programmed and can work with the help of a microcontroller to integrate and control a device or home appliance automatically and efficiently. The purpose of creating this technology is to facilitate energy savings, get comfort and be able to control it only with a smartphone. In the research entitled "IoT based Smart Home Automation System using Sensor Node". This stage of development will use several microcontrollers as sensor nodes. Microcontroller nodes will control such as lights, doors, fans. In this study, it used several types of sensors such as RFID, reed switch, temperature and microcontrollers that will be used by the ESP8266 MCU Node. All data from sensor readings will be sent to the Blynk server. As a data viewer and control center will use the Blynk application. This can also increase the selling price of the house to be sold by the developer.

Smart Home Automation System Based on Li-Fi Technology

In general, home automation means controlling the utilities and features of the household appliances. To achieve this most automation systems use Wi-Fi as a communication technology. But when it comes to Wi-Fi the overall setup cost will be higher and it also not possible to connect all the household appliances to the network. For that we had proposed a system called smart home automation system based on Li-Fi technology. Since its Li-Fi, a VLC, we can use our domestic household LED lights as a transmitting source. This system will control the power up function of the appliances. And the overall setup of this system is very simple on both the hardware and software sides. The specific light encoded data will be transmitted by the LEDs and decoded by photodiode at the receiver section. By implementing this Li-Fi technology in home automation will bring the new era of automation with simple, speed, cost-effective and secure features. And this will be the dual benefits of both luminance and automation in a single implementation setup. And on the security side also it will provide secure communication with the ability to be impenetrable through physical objects because of the nature of light. Not only smart devices, every electrical device can be operated with this technology implementation. Key Word: Home Automation; LI-FI; Sensor; Connection; Future

Access Control and Voice Response in IoT Based Home

The goal of this project is to design a smart phone application-controlled home automation system. The system will monitor and manage several elements of the house, including lighting, and security, using a combination of sensors, microcontrollers, and communication protocols. The system will be created to be user-friendly, secure, and economical with energy. Users will be able to establish routines, get notifications, and remotely operate and monitor their house via the smart phone app. To further improve the system's functioning, the study will investigate the integration of voice assistants and machine learning techniques. The ultimate objective of this project is to develop a complete home automation system that offers its consumers comfort, convenience, and peace of mind. Keywords: Access control system Home automation, Microcontrollers Node MCU, Voice assistants.