Nadarajoo, Navindran (2023) Design and analysis of home assiatant based on Raspberry Pi for smart home automation. Masters thesis, Universiti Teknikal Malaysia Melaka.
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Abstract
With the evolution of technology influencing every aspect of daily life, home automation has emerged as a popular option. Supported by the IoT, smart home technology integrates electronics and information technology to streamline everyday tasks and enhance convenience and efficiency. These internet-connected devices operate autonomously, meeting consumer preferences and demands, while providing numerous benefits to homeowners of all age groups, such as increased security, comfort, connectivity , and energy management. Home Assistant, an open-source program, is a prevalent choice among modern home automation systems. With a strong emphasis on local control and privacy, Home Assistant has garnered a significant user base. The platform can be integrated with Raspberry Pi using Hass.io, a managed operating system, offering additional capabilities for home energy management. This paper's primary objective is to utilize Home Assistant running on Raspberry Pi to create a home energy management system. The integration of Home Assistant with household appliances simplifies the process of understanding and optimizing energy usage in homes. By leveraging Home Assistant's capabilities and the Raspberry Pi's technology, this project aims to enhance energy management practices and empower users to make informed decisions about their energy consumption, promoting sustainable living and efficient resource utilization. Firstly, the project focuses on programming the appropriate script integration to efficiently handle household tasks through the Home Assistant system, effectively transforming it into a Home Automation Hub. Secondly, the project aims to develop a user-friendly Graphical User Interface (GUI) that provides centralized control over all installed smart devices in the home. The project aims to create a comprehensive and efficient home automation system using Home Assistant. The implementation of the project will contribute to enhancing smart home management, offering users enhanced control, security, comfort, energy efficiency, and connectivity, ultimately providing a seamless and intelligent living experience. Step-by-step phases of a process in a logical order, enhancing understanding through visually connected boxes and arrows. Initiating and implementation process was carried out by identifying the system integration for optimal script and operating system selection. Overall, the project effectively employed the Raspberry Pi 4 Model B as the central device to implement and evaluate the Home Assistant-based smart home automation system, offering energy-efficient and versatile control capabilities for enhancing home automation functionalities. Based on the surveyed data, approximately 68% of the respondents are aware of home automation, 25% of the participants have not heard of home assistant, while 18.8% are familiar with it, and an encouraging 56% express interest in implementing it in their homes in the future. Regarding security, all responded highly due its importance. Furthermore, it is evident that around 31% of respondents desire the implementation of all five elements of home automation in their homes, while approximately 25% prioritize either energy or security-related elements over others, highlighting their significance in their decision-making process. The necessary recommendations for improvement include making third-party coding scripts easily accessible for user convenience, implementing facial recognition for unlocking due to security concerns, acquiring a Wi-Fi extender with larger coverage for enhanced connectivity, and ensuring seamless integration of devices by simplifying the process of obtaining IP addresses.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Home automation, Home automation, Computer programs, Household electronics, Raspberry Pi (Computer) |
| Divisions: | Library > Tesis > FKP |
| Depositing User: | MUHAMAD HAFEEZ ZAINUDIN |
| Date Deposited: | 30 Jul 2024 14:52 |
| Last Modified: | 30 Jul 2024 14:52 |
| URI: | http://eprints.utem.edu.my/id/eprint/27149 |
| Statistic Details: | View Download Statistic |
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