Car Parking Slot Detection using Convolutional Neural Networks

Finding a parking spot has become a problem that must be addressed; it takes time and effort. Finding a parking place, especially in metropolitan locations, is a massive pain. This study tries to build one such parking system that decreases the inconveniences of parking in a variety of ways. The study describes a system that uses a Convolution Neural Network (CNN) machine learning model to evaluate parking slots in a parking spot as vacant or filled. Parking troubles are not restricted to creating annoyance to cars; they may also develop far larger and more widespread issues, affecting a considerably larger number of people and the environment. As a result, having a reliable parking infrastructure is essential. The technique presented in the research communicates parking information to a driver in advance, considerably decreasing the time spent waiting for a car.