Performance analysis of ZigBee based real time Home Automation system

Home automation system has achieved an enormous reputation in recent years, as day-to-day life is getting simpler due to the speedy growth of modern technology. Various implemented systems have been offered in the sphere of Home Automation but have apparently failed to provide cost-effective solutions for the same. In this paper, we provide a low-cost smart Home Automation and Security System (HASS) using Wireless Fidelity (Wi-Fi), and Bluetooth. These materialize the concept of internetworking of smart devices. A Wireless Sensor Network (WSN) based on Wi-Fi is considered to monitor and control the smart environment, safety as well as electrical parameters of a smart interconnected home. The Android application-based Graphical User Interface (GUI) on a Smartphone is used to give facility to users for seamless control over the devices in a smart home. It may also consist of home security for example access control and alarm systems. When connected to the Internet, home devices are an important element of the Internet of Things (IoT). Home security includes both the security hardware placed on a property and individuals' personal security practices. Security devices consist of a door locking, alert alarm, lighting, motion detectors, and security camera system. Additionally, several special features include such as ensuring windows are closed, each door is locked, all alarms are activated, and extra keys are not secret outside.

Home automation is a modern technology that helps to enjoy comfortable living conditions inside the home. With home automation, data can be instantly collected and passed between devices and analyzed simultaneously. By connecting the home appliances with the internet, they can be easily accessed from anywhere. In the home automation system, settings are feasible through smartphones or other remote-control devices. This paper gives the design and implementation of a new voice- controlled home automation system that uses Google Assistant for giving user’s voice commands as input. It is a low cost and flexible home automation and monitoring system. It enables the user to use a home automation system based on the Internet of Things (IoT). Home appliances like fans and lights can be controlled. The fundamental purpose of this project is to control electronic appliances based on the situational demands of the user.

This paper presents an experimental evaluation of ZigBee and DigiMesh networks; a two well-known and widely used Wireless Mesh Networks architectures. The performance metrics used were the throughput, Round Trip Time, Received Signal Strength Indication, and Mesh Routing Recovery Time. The conducted experiments show that DigiMesh have better throughput than ZigBeee networks. However, the later outperforms DigiMesh based networks by having lower Round Trip Time, higher Received Signal Strength Indication, and it needs less time to recover from a failure node. These features make ZigBee a better choice for applications that require less delay and need longer communication range, while DigiMesh based networks are better used for networks with high throughput requirements.

Non line of sight (NLOS) conditions significantly degrade the accuracy of Wi-Fi-Based indoor positioning systems (IPS). Although round-trip time (RTT) is generally more reliable than the received signal strength indicator (RSSI), it remains vulnerable to attenuation and multipath; moreover, dense RTT-compatible AP deployments may threaten scalability. This paper proposes a fingerprinting-based IPS that achieves high accuracy in NLOS scenarios, while remaining scalable and lightweight for Internet of Things (IoT) devices. By combining RTT, its standard deviation, and RSSI, accurate position estimates are obtained with only two RTT requests, reaching 93% accuracy and a 62 cm root mean squared error (RMSE) despite harsh conditions.

The adoption of home automation systems in buildings faces limitations due to their cost, integration complexity, and protocol heterogeneity, which hinders the development of accessible solutions based on embedded devices to improve interaction in environments within buildings or homes. The literature review indicates that the selection of hardware and communication protocols in home automation systems considers factors such as cost, available infrastructure, and application context. In addition, approaches are identified that prioritize security, wired or wireless connectivity, and affordability. This paper presents the development of an affordable home automation system for building automation in Lima, using the ESP32 microcontroller and internet of things (IoT) technologies. The objectives focus on hardware design, implementation of control algorithms, remote monitoring interface, and validation in a simulated environment. The solution includes Wi-Fi connectivity, a cloud-based MySQL database, and a web interface. Key findings include the home automation system, integrated with Flask technology and web services, enabling monitoring and control via a responsive web interface, demonstrating its operability and ensuring lossless data transmission.

With the advent of internet-of-things (IoT)-based home automation systems, time synchronization techniques for low power sensor modules are in high demand. The constrained application protocol (CoAP) was recently standardized for sensor networks by IETF and is becoming widely adopted for home automation systems by ETSI, OMA, and oneM2M. The network time protocol (NTP) is not applicable to home automation systems due to its limited computing resources. This paper proposes a lightweight time synchronization algorithm for CoAP-based home automation system networks. The CoAP option field and a shim header are used to include time-stamps in the home automation system. The proposed scheme can thus be applied to both IP-based and non-IP-based home automation systems. In experiments with several household devices having non-IP communication interfaces, experimental results show that the proposed technique gives an average error of 1 ms and a network overhead reduction of 17% when compared to the ideal NTP service.

This paper proposed awareness home automation system (HAS) based on mobile sensing. Some of the ideas have been proposed in HAS but most of them still requires human intervention such as click the button, voice commands, etc. We want to design and develop HAS which can understand and comprehend the user desires without having to wait for commands from the user (awareness HAS). In this research we exploit two of android sensors. First, accelerometer sensor for identification and activity recognition, second, magnetic field for user indoor positioning system and defined the context related to physical environment. This paper presenting the result of used both of the sensors for developing awareness HAS.

Several home automation systems have been rapidly introduced in the recent years. However, the consumer adoption of home automation systems has been immensely slow. Moreover, most home automation systems available in the market are designed for western countries and do not have certain features that are crucial for consumers in tropical countries like Malaysia. Therefore, this paper identifies the possible criteria for this slow adoption and evaluates the potential of Intel Galileo for addressing these problems. Four popular home automation technologies are analysed and surveys are conducted to identify the needs of electricity and water consumers in Malaysia. A low cost, secure, user-friendly, easily installed and flexible Intel Galileo based home automation system that caters the needs of Malaysians is presented. The system is integrated with an Android application and uses a Wi-Fi network. To demonstrate the feasibility and effectiveness of the proposed system, the design and prototype implementation of a basic home automation system based on the Intel Galileo is developed and evaluated based on several tests and interviews. The proposed system can be used as a reference to increase consumer adoption of home automation systems in tropical countries.

A home automation system controls lighting, temperature, multimedia systems, and appliances. Since these devices and sensors are connected to common infrastructure, they form the Internet of Things. A home automation system links multiple controllable devices to a centralized server. These devices have a user interface for controlling and monitoring, which can be accessed by using a tablet or a mobile application, which can be accessed remotely as well. Ideally, anything that can be connected to a network can be automated and controlled remotely. Smart homes must be artificially intelligent systems that need to adapt themselves based on user actions and surroundings. These systems need to carefully analyze the user needs and the conditions of the surroundings in order to predict future actions and also minimizes user interaction. Traditional home automation systems that provide only remote access and control are not that effective in terms of being `smart', so in this paper we put forward the use of concepts of different machine learning algorithms along with computer vision to shape together a smart learning automated system that controls lighting, sound and other devices based on the user's emotion.

In this paper we present the results of real-life localization experiments performed in an unprecedented cooperative and heterogeneous wireless context. These measurements are based on ZigBee and orthogonal frequency division multiplexing (OFDM) devices, respectively endowed with received signal strength indicator (RSSI) and round trip delay (RTD) estimation capabilities. More particularly we emulate a multi-standard terminal, moving in a typical indoor environment, while communicating with fixed OFDM-based femto-base stations (Femto-BSs) and with other mobiles or fixed anchor nodes (through peer-to-peer links) forming a wireless sensor network (WSN). We introduce the measurement functionalities and metrics, the scenario and set-up, providing realistic connectivity and obstruction conditions. Out of the experimental data, preliminary positioning results based on cooperative and geometric algorithms are finally discussed, showing benefits through mobile-to-mobile cooperation, selective hybrid data fusion and detection of unreliable nodes.

Accurate human counting in indoor environments is essential for optimizing people-centric applications, such as crowd management, disaster response, and monitoring in settings like shopping malls and healthcare facilities. Traditional vision approaches face challenges with poor lighting conditions and raise privacy concerns. WiFi-based solutions enable device-free human counting by detecting disruptions in wireless signals caused by human presence. However, methods using received signal strength indicator are unreliable due to physical obstructions, multipath fading, radio interference, and fluctuating access point power. While WiFi channel state information-based systems are more sensitive to environmental changes, they lack standardization, limiting their practicality. To overcome these limitations, this paper presents Time4Count, an innovative device-free indoor human counting system that leverages round trip time measurements to achieve high accuracy and scalability. Time4Count capitalizes on human-induced fluctuations in signal propagation time to accurately estimate the number of individuals in a space. By employing a multivariate transformer-based feature extraction method, the system effectively mitigates non-line-of-sight errors and signal distortions, ensuring robust performance even in cluttered indoor environments. Additionally, Time4Count integrates spatial discretization and multi-label classification techniques, enabling it to count an unlimited number of individuals in real-time. The system was rigorously evaluated in two realistic, cluttered environments using commodity hardware, involving up to 15 participants. Experimental results reveal that Time4Count achieves an high counting accuracy of 92.7%. To our knowledge, Time4Count is the first RTT-based indoor counting system, providing a precise solution for indoor monitoring. Implementation is available at: https://github.com/mclab-osaka/time4count.

Electricity is one of the most important aspects of human survival on the planet. Due to advancements in communication technology, the Home Automation System is gaining popularity. The smart sensors can sense physical parameters and can help in creating a better environment to live in. With advancement in technology and interlinking of the devices with android app, security of data has become the most important parameter that has to be considered while designing such smart systems emphasis has to be given to design them as energy efficient system. The proposed system is an IoT based energy efficient automation system with security features for home and industrial automation. The appliances in this system can be controlled from anywhere, i.e., in the local network without the internet as well as over the internet. To make the system more flexible different features like mood switching, dimming, timer controlled, alexa assistant etc. was implemented. The proposed system will be long range communication system using LoRa protocol with a smaller number of hardware components required for the automation system. It will be a modernize solution and no expert worker will be needed, thus it will reduce the overall cost of the automation system.

This research focuses on the manufacture of home automation systems to optimize the use of electricity. Home automation system has four features, namely automatic control, manual control, control based on the habits and customs control based on fuzzy logic and method Tsukamoto. Fuzzy logic Tsukamoto will calculate the temperature that should be spent by the AC, using input from sensors LM35 that are indoors and outdoors, so that the temperature of the issued AC was not too hot and too cold home automation system features 3 sensors which PIR sensor, sensor LM35 and LDR sensor that will be used as input data on the system. Home automation system will control electrical equipment, namely air conditioning and lighting optimally. Keywords: Arduino Uno R3, Controlling, Home Automation, Fuzzy Logic

The proliferation of consumer Home Automation Systems (HAS), which is increasingly based on the Internet of Things (IoT) architecture, comes with added costs for the additional electrical energy required to power the automation interfaces and the standby energy consumption required to maintain connectivity and/or “smartness”. In this article, we use a bottom-up approach to develop novel system-level energy consumption models for consumer HAS devices and quantify the energy consumption for a typical HAS. We then assess the potential impact on global Information and Communications Technology (ICT) energy use. We show that, on average, HAS may consume over one-third of the annual energy used in a mid-sized home, with non-trivial impact on the global ICT energy footprint.

Home automation has come a long way thanks to the development of smart technologies, which have increased efficiency, security, and convenience. The creation of a Smart Home Automation System (HAS) that allows for the remote control of appliances and strong protection against intruders and fire threats is detailed in this article. In this study, we build a home automation system that can be controlled remotely through a web browser. The system uses an internet connection and SMS alerts. The GUI is a web page. Regardless of the user's location, our proposed model for a monitoring and controlling device that warns them via Internet and SMS notification for security purposes tries to solve the difficulty. Various sites were examined to determine the prototype's efficiency, and the results revealed that the prototype was most effective at sites with the strongest signals. This research paper explores HAS in detail, including its technical foundations and the ways it can revolutionize human-home interaction for the better, leading to a future that is smarter, safer, and more environmentally friendly.