The development of smart home systems integrating Internet of Things (IoT) devices and machine learning algorithms represents a significant advancement in residential automation. This thesis report presents a comprehensive study on the design, development, and evaluation of a Smart Home Automation platform. The research focuses on creating an IoT-based system capable of seamlessly integrating various devices, such as sensors, lighting, and smart appliances, to enhance automation and energy efficiency within modern homes. Key components of the study include the selection of sensors and actuators, hardware setup, mobile application development, and machine learning model implementation. The report delves into the system architecture, performance evaluation of the smart home prototype, analysis of the mobile application functionality, and evaluation of the machine learning model. Findings from the study contribute valuable insights to the field of smart home technology, emphasizing achievements, limitations, and future directions for research and development.