Detection of Empty Slots in Car Parking System Using Neural Network Method

Abstract

There are many transportation equipment such as a car, a motorbike in Indonesia. Increasing the volume of vehicle users will increase parking activities in every public place. Parking is a condition of a vehicle that is not temporary. The current parking system still uses a conventional parking system that only uses parking lots and parking attendants who control each vehicle that enters, and often do not pay attention to the capacity of parking space that has been provided and often drivers go around first to find an empty parking lot. Therefore, detection of empty slots in the parking system is needed. To obtain this information, this study using a neural network method. The neural network is one of the information processing systems designed by imitating the workings of the human brain in problem-solving. The purpose of this research is to determine which car parking slots filled or empty parking slots. The results of detection of car parking slots using a neural network method were carried out experiments on 20 objects with as many as 12 slots and with three slots that are rectangles, squares, and traingles. In the square slot with an area of 784 cm2 get accuracy results 100%, rectangular slots with an area of 3.608 cm2 obtained accuracy 95% and a traingle slot with an area of 1.804 cm2 obtained an accuracy 90%.