This research develops a smart home automation system that utilizes advanced AI technology and the Internet of Things (IoT) to create added value in energy management and user comfort. The system is implemented using Python on a Raspberry Pi to enable the remote control of household devices like lights, TVs, and air conditioners which can be accessed through any web browser within the local network without any special software needing to be installed on the user’s device. The execution of the design is defined in two stages. The first stage concerns the control of appliances in real-time using IoT technology with an emphasis on conserving energy and remote control. The second stage introduces a linear regression machine learning model which uses historical data captured in a specialized database to predict future usage. This capability of the system enables automatic control of energy consumption based on the users’ activities and the surrounding conditions. The application of IoT sensors and machine learning algorithms offers an affordable solution to automated home control. These features not only aid in the reduction of power consumption, but create added comfort to the user by responding to their usage trends. By addressing these issues the research contributes to the development of smart home systems based on a database-driven approach, where more powerful AI models can be utilized to enhance automation, security, and efficient use of energy resources.
Haq et al. (Sat,) studied this question.