Commonly soft sensors are based on control theory and also receive the name of state observer.
The interaction of the signals can be used for calculating new quantities that need not be measured.
Soft sensors are especially useful in data fusion, where measurements of different characteristics and dynamics are combined.
Well-known software algorithms that can be seen as soft sensors include Kalman filters.
More recent implementations of soft sensors use neural networks or fuzzy computing.