The advent of smart home technology has revolutionized the way individuals communicate with their living spaces, offering efficiency, convenience, and comfort. The integration of brain-computer interface technology within smart home environments presents a promising avenue for transforming human–computer interaction paradigms. This review paper synthesizes current research findings on optimizing smart home user interfaces through humancomputer interaction utilizing Electroencephalography based BCI technology. EEG-based BCIs offer a novel approach to interface design by directly interpreting users’ neural signals, thereby enabling seamless interaction with smart home devices. By leveraging EEG signals to interpret users’ cognitive states and intentions, BCI offers a direct pathway for intuitive communication between humans and devices, bypassing traditional input modalities. The paper examines a few explicit key components such as signal acquisition, feature extraction, feature selection, classification algorithms, and system integration. Furthermore, the review evaluates the effectiveness, challenges, and future prospects of EEG-based BCIs in optimizing human–computer interface within smart home ecosystems. Insights from this review contribute to the understanding of how EEG-based BCIs can revolutionize user interaction paradigms, leading to more intuitive, efficient, and personalized smart home environments. This work presents a comprehensive study on the proposed topic by consolidating useful information from various sources and exhibiting it in a single paper to provide quality data to the novice researchers to help them in this field of research.