The recent advancements in the integration of artificial intelligence and wearable technologies are significantly enhancing the capabilities of smart home environments, particularly in the context of personalized healthcare. There is a notable shift towards creating unified platforms that leverage multimodal data inputs, such as voice, visual, and sensor data, to provide comprehensive and adaptive support for users with specific health needs. These platforms are not only enhancing the accuracy and efficiency of health monitoring but also enabling real-time interventions that improve user satisfaction and outcomes. Additionally, the development of personalized multimodal large language models is expanding the scope of intelligent assistants, making them more adaptable to individual preferences and requirements. This trend is particularly evident in the design of smart home assistants for the Deaf and Hard-of-Hearing community, where multimodal inputs and augmented reality are being integrated to ensure accessibility and inclusivity. The deployment of large language models on mobile devices is also gaining traction, promising more natural and personalized user experiences while enhancing data privacy and security through local inference capabilities. Overall, the field is moving towards more integrated, personalized, and accessible solutions that leverage advanced AI and multimodal technologies to address diverse user needs.