A Framework for Secure, Energy-Efficient Smart Buildings: Dynamic Security and Efficiency Enhancements

Integrating IoT-based technologies has greatly increased the significance of smart buildings since they can control building operations, growth comfort, and advance energy effectiveness. Cybersecurity and energy issues are, however, exacerbated by these innovations. This study grants a innovative method to smart building security and energy adaptability that tackles both problems head-on. Machine learning algorithms understand energy usage trends while boosting security setup; real-time power meters; and alarms for security violations are all part of it. The architecture is adaptable, so it can handle shifting security regulations and needs without impacting power usage. It reduces energy consumption and guarantees security against attacks by utilising decentralised sensor networks, encrypted communication, and self-organising dynamics. Commercial, residential, small, medium, and big office buildings, as well as megastructures, can all benefit from the suggested approach. The framework will be enhanced in subsequent work to incorporate automatic upkeep capabilities for critical building systems and to handle future cybersecurity threats.