Detection parking Spaces by using the AlexNet Algorithm

Abstract

Finding an empty parking space in a crowded area is very stressful due to congestion. In the absence of
empty space, leads to fatigue before the main activity, increased fuel consumption, which leads to
increased pollution, and increased traffic due to the search for empty space. Therefore, it was necessary
to have a system that would help drivers know the condition of each parking space. Empty or occupied
with a vehicle. Where the empty and occupied spaces are calculated and determined so that the system
displays a map of the empty spaces on the screen that is placed in a suitable place in the parking lot to
facilitate directing the driver to the vacant parking spaces and warn if all the parking spaces are
occupied. All this is done through images taken from the surveillance cameras in the parking lot. We find
that the advantages of using vision-based systems over other existing systems are threefold. First There is
no need to update the infrastructure of the parking lot, provided that the place is equipped with
surveillance cameras that monitor the parking spaces covering the entire place. Secondly, camera-based
systems give the exact location i.e. a detailed map of the vacant car parks which are good and necessary
vacant lots. Third, camera-based methods are highly applicable in street parking spaces and residential
areas. Our system achieved excellent results as the average prediction accuracy was 99. 89% and
99.78% on the PKLot data set and the local data set, respectively. This high accuracy and low price makeit a good alternative to systems that use sensors.