Conceptual architecture for imparting AI with olfaction: Integration of electronic noses, aroma generators and LLM

This paper proposes a conceptual architecture to integrate olfaction into AI using an electronic nose, an odor generator, and large language models like ChatGPT. The electronic nose detects odors via chemical sensors, while the aroma generator reproduces similar scents remotely. Large language models enhance real-time system calibration and provide a natural language interface, addressing issues like signal standardization, sensor calibration, and data interpretation. Potential applications span industry, medicine, VR/AR, and e-commerce. The outlined workflow and challenges pave the way for prototyping and real-world testing to redefine AI's interaction with the physical and digital worlds.