  Glitches are the observational manifestations of superfluidity inside neutron
stars. The aim of this paper is to describe an automated glitch detection
pipeline, which can alert the observers on possible real-time detection of
rotational glitches in pulsars. Post alert, the pulsars can be monitored at a
higher cadence to measure the post-glitch recovery phase. Two algorithms
namely, Median Absolute Deviation (MAD) and polynomial regression have been
explored to detect glitches in real time. The pipeline has been optimized with
the help of simulated timing residuals for both the algorithms. Based on the
simulations, we conclude that the polynomial regression algorithm is
significantly more effective for real time glitch detection. The pipeline has
been tested on a few published glitches. This pipeline is presently implemented
at the Ooty Radio Telescope. In the era of upcoming large telescopes like SKA,
several hundreds of pulsars will be observed regularly and such a tool will be
useful for both real-time detection as well as optimal utilization of
observation time for such glitching pulsars.
