This paper discusses the use of a possibilistic framework for system monitoring tasks where a system model jointly with measurements is given as a set of algebraic equations. Uncertainty is handled via the introduction of slack variables and an optimization-based (linear or quadratic programming) approach is proposed to compute the possibility distributions of the internal variables to be monitored. A case study on a bio-engineering problem is presented.