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In recent years, in industry, whether in the application of advanced control strategies or in the direct control of product quality, one of the most challenging problems has been the difficulty in performing online, real-time measurements of product quality variables. Soft sensing has gradually been developed precisely to address the problems of real-time measurement and control of such variables. Online continuous monitoring technology is derived from the inference estimator in inference control; it involves collecting certain easily measurable variables (also known as secondary or auxiliary variables) and constructing a mathematical model that uses these easily measurable variables as inputs to estimate the difficult-to-measure primary variables (also known as dominant variables). Soft sensing enables real-time online measurement of the parameters that need to be monitored, and it automatically adjusts the parameter settings so that the actual values match the requirements set for production. This helps to reduce the rate of defective products, improve product quality, and lower energy consumption. With the widespread adoption of online continuous monitoring technologies, it will drive an expansion of the scope of industrial automation and improve economic efficiency. Of course, my view isn’t entirely comprehensive; feel free to contact me if you have any suggestions. The spread of soft measurement is the first step toward achieving industrial automation! What do you experts think?