  Chromospheric swirls are considered to play a significant role in the
dynamics and heating of the upper solar atmosphere. It is important to
automatically detect and track them in chromospheric observations and determine
their properties. We applied a recently developed automated chromospheric swirl
detection method to time-series observations of a quiet region of the solar
chromosphere obtained in the H$\alpha$-0.2 \r{A} wavelength of the H$\alpha$
spectral line by the CRISP instrument at the Swedish 1-m Solar Telescope. The
algorithm exploits the morphological characteristics of swirling events in high
contrast chromospheric observations and results in the detection of these
structures in each frame of the time series and their tracking over time. We
conducted a statistical analysis to determine their various properties,
including a survival analysis for deriving the mean lifetime. A mean number of
146 $\pm$ 9 swirls was detected within the FOV at any given time. The mean
surface density is found equal to $\sim$0.08 swirls$ $Mm$^{-2}$ and the
occurrence rate is $\sim$10$^{-2}$ swirls$ $Mm$^{-2}$ min$^{-1}$. These values
are much higher than those previously reported from chromospheric observations.
The radii of the detected swirls range between 0.5 and 2.5 Mm, with a mean
value equal to 1.3 $\pm$ 0.3 Mm, which is slightly higher than previous
reports. The lifetimes range between 1.5 min and 33.7 min with an arithmetic
mean value of $\sim$8.5 min. A survival analysis of the lifetimes, however,
using the Kaplan-Meier estimator in combination with a parametric model results
in a mean lifetime of 10.3 $\pm$ 0.6 min. An automated method sheds more light
on their abundance than visual inspection, while higher cadence, higher
resolution observations will most probably result in the detection of a higher
number of such features on smaller scales and with shorter lifetimes.
