Converging Intelligent Architectures for Secure and Adaptive Smart Homes:A Review of AI, Privacy, and Security Frameworks

Combining cutting-edge technologies, especially for building services and devices, is bringing major changes to intelligent homes and quickly moving the smart home solutions field forward. For the benefit of smart environments in coming years, this study analyzes the opportunities from adding LiDAR-AR systems, Digital Twin tests, combining AI home intelligence, blockchain safe authentication, quantum secure data transfer and Federated Learning data analysis. All of these methods are meant to resolve individual issues, including automatic control, data privacy in learning, accurate location mapping, detailed simulations and sharing trustworthy data. The most important achievement of this study is the design of a detailed plan for combining the new technologies safely and flexibly in a smart home. With access to live data from digital twins and high-quality spatial info from LiDAR-AR technology, these AI systems can deliver fast and well-informed decisions that respond to specific locations. This way of learning keeps user data private because artificial intelligence training happens on different devices instead of all together. In addition, the software relies on strong blockchain authentication and MQTT protocols that use quantum technology to guarantee trusted identity and secure communications as online dangers develop. Uniting all these developments results in an improved method for building intelligent rooms that are smart, stay flexible, value privacy, keep people safe and can grow with changing technology. This approach provides a good base for further development of autonomous home systems.

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