A general trend in the experimental programmes of present day Tokamaks, and of JET in particular, is the constant increase in the number of parameters to be controlled in real time, to satisfy the machine protection requirements on the one hand and to improve performance on the other. Since the amount of data collected is also increasing at least at a rate compatible with the Moore law, significant developments are required in the field of real time algorithms particularly for magnetic reconstructions, disruption prediction and image processing. A new real time equilibrium code called EQUINOX, using internal and external measurements of the magnetic fields, has been qualified on JET. It can provide reconstructed accurate equilibria about every 50ms on a 2GHz PC. An advanced disruption predictor, based on machine learning tools, has been deployed using inputs selected with a genetic algorithm. Its success rate remains of the order of 94% for up to 170ms before the occurrence of the disruption. Nonextensive entropies, which are more sensitive to long range correlations, seem to be useful in detecting vibrations in the videos of JET cameras, both visible and infrared.