An artificial neural network (NN)-based technique for smart sensors operating in harsh environments is proposed that automatically calibrates, linearizes and compensates for the adverse effects due to nonlinear response characteristics and complex nonlinear dependency of the sensor characteristics on the environmental parameters. To show the potential of the proposed NN-based technique, we provide simulation results of a smart capacitive pressure sensor (CPS) operating under a wide temperature range.