Real-Time DNN-Driven IoT Control for Intelligent Chatbot Interaction

Following the release of ChatGPT-4, chatbots have emerged as a key advancement in AI, enabling users to interact via text or voice to perform a range of functions-answering questions, executing commands, and retrieving information. By integrating with machines, AI-based chatbot systems can perform actions, provide status updates, track performance, and troubleshoot-all through natural language, without requiring technical expertise. The AI chatbot makes use of Natural Language Processing technology to translate English user input into executable categories for accurate response generation. In this research, we propose a system that uses Information Extraction combined with Deep Neural Networks (DNNs) to create its design and implements ChatGPT API for improved conversational functions. We have developed a group of specialized DNN models to support execution by processing various types of user commands. Our proposed system demonstrates 96 % precision when interpreting user meaning while it shows <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{9 4 \%}$</tex> precision in executing commands properly.