the rapid integration of the Internet of Things (IoT) with artificial intelligence has unlocked new opportunities to developadaptable, multi-domain artificial intelligence (AI) agents. However, the design of many AI agents for specific tasks limits their ability togeneralize across different applications and environments. This paper introduces a generic artificial intelligent agent that utilizes IoT anddeep learning, enabling autonomous adaptation to diverse domains such as smart homes, healthcare, industrial automation, and agriculture.The agent leverages IoT sensors for real-time data collection, while deep learning models process and analyze this data to make intelligent,context-aware decisions. Using a combination of initial training and domain adaptation techniques, the agent can learn to recognize patternsand perform tasks across diverse environments. This research proposes an intelligent facial identification and recognition system poweredby deep learning. It automatically updates the identification records of individual personnel based on the results generated by the recognitionprocess. Utilizing deep learning models, the system performs both facial recognition and object detection, ensuring high accuracy andreliable performance.Keywords: natural language processing (NLP),deep learning, IoT, Face Detection and convolutional neural networks (CNN)