<![CDATA[The development of digital technology demands smarter and more integrated security systems, particularly for critical infrastructure such as power plants, which play a crucial role in national energy distribution. Power plant monitoring systems that still use conventional authentication methods like static passwords and RFID have weaknesses such as the risk of theft, forgery, and access misuse. Furthermore, the lack of integration with Internet of Things (IoT) systems means that the monitoring process is not fully real-time and potentially causes delays in detecting intrusions and security threats. This situation highlights the need for a layered security system capable of accurately and dynamically verifying user identity. This research aims to implement facial recognition technology and the Time-Based One-Time Password (TOTP) algorithm as a layered authentication system for IoT-based power plant monitoring. The system is designed to combine facial biometric verification with a time-based OTP code that can be generated independently of an internet connection. The integration of these two methods is expected to improve access security by minimizing the risk of identity spoofing, credential theft, and cyberattacks. The methods used include system design, hardware and software implementation, and performance testing of authentication and IoT integration. The expected outcome of this research is the creation of a more adaptive, reliable security system capable of recording access activity in real time. Therefore, the implementation of IoT-based facial recognition and TOTP can be an effective solution for enhancing protection for power plant monitoring systems, which are vital national assets.]]>
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