GENAI-POWERED VOICE ASSISTANTS FOR SMART HOMES

Abstract

The rapid advancement of Generative Artificial Intelligence (GenAI) is transforming the capabilities of voice assistants in smart home environments. This paper explores the integration of GenAI-powered voice assistants that go beyond traditional command-based systems to enable more natural, context-aware, and personalized interactions. By leveraging large language models, these assistants can understand complex user intents, engage in conversational dialogue, and adapt to individual preferences over time. The proposed system architecture combines speech recognition, natural language understanding, and generative response mechanisms to create a seamless user experience. It also incorporates IoT device integration, allowing centralized control of lighting, security, climate, and entertainment systems through intuitive voice commands. Additionally, the study addresses key challenges such as data privacy, security, latency, and system reliability. Experimental analysis demonstrates improved user satisfaction, efficiency, and flexibility compared to conventional rule-based voice assistants. The findings suggest that GenAI-powered systems represent a significant step toward fully autonomous, intelligent smart homes capable of proactive assistance and decision-making. Generative Artificial Intelligence (GenAI) is redefining the functionality of voice assistants by enabling advanced contextual understanding and dynamic response generation. This paper presents a GenAI-powered voice assistant designed for smart home ecosystems, integrating speech-to-text processing, transformer-based language models, and IoT device orchestration. Unlike conventional assistants, the system supports multi-turn conversations, intent prediction, and adaptive learning from user behavior. The proposed framework enhances automation by enabling proactive decision-making and personalized control of home appliances.