  With the number of vehicles continuously increasing, parking monitoring and
analysis are becoming a substantial feature of modern cities. In this study, we
present a methodology to monitor car parking areas and to analyze their
occupancy in real-time. The solution is based on a combination between image
analysis and deep learning techniques. It incorporates four building blocks put
inside a pipeline: vehicle detection, vehicle tracking, manual annotation of
parking slots, and occupancy estimation using the Ray Tracing algorithm. The
aim of this methodology is to optimize the use of parking areas and to reduce
the time wasted by daily drivers to find the right parking slot for their cars.
Also, it helps to better manage the space of the parking areas and to discover
misuse cases. A demonstration of the provided solution is shown in the
following video link: https://www.youtube.com/watch?v=KbAt8zT14Tc.
