Abstract
The integration of real-time embedded systems into smart building automation has revolutionized how buildings are managed for efficiency, safety, and user comfort. These systems enable autonomous control over critical building operations such as lighting, HVAC, energy consumption, security, and occupancy detection. With the rise of IoT and edge computing, modern embedded platforms now support low-latency decision-making and adaptive learning algorithms, creating responsive, energy-efficient environments. This paper explores the architectural principles, key components, and operational strategies of real-time embedded systems for smart building applications. It further examines implementation challenges, including interoperability, security, and scalability, while proposing future directions in AI-driven automation.
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