Digital twins integrate various technologies such as IoT sensors, machine learning, and big data analytics to gather and analyze data from the physical catalytic system. This data is then used to create a dynamic model that mirrors the physical system's behavior. Advanced algorithms continuously update the digital twin, ensuring it remains an accurate representation of the real-world process.
