Artificial Intelligence-Driven Smart Home Systems: Technologies, Applications and Future Challenges

Abstract

With the continuous development of artificial intelligence (AI) technology, smart home systems have gradually evolved from traditional automated control modes toward intelligent systems with environmental perception, autonomous decision-making, and proactive service capabilities. However, existing smart homes still face problems such as a single mode of interaction, insufficient intelligent proactivity, and limited scene adaptability. Based on relevant research results in recent years, this paper systematically reviews the application progress of AI technology in the smart home field, focusing on key directions such as the Internet of Things (IoT) architecture, multimodal interaction, intelligent decision-making, edge computing, and data security. The review shows that AI technology has effectively improved the perception, interaction, and decision-making capabilities of smart home systems. Among these technologies, large language models (LLMs) enhance natural language understanding and user interaction capabilities, edge computing improves the real-time response efficiency of the system, and technologies such as blockchain provide new solutions for data security. At the same time, smart homes still face challenges in privacy protection, model reliability, cross-device collaboration, and standardization. In the future, modern smart home systems should be further integrated with artificial intelligence technologies, change traditional basic interaction modes, and promote the development of smart homes toward greater intelligence, security, and adaptability.