A Systematic Parking System Using bi-class Machine Learning Techniques

Mismanagement of parking space is one of the major issues in this modern world. Hence an efficient parking system is to be designed to overcome this global issue. In this work, real-time data is used which has been collected from the survey by asking a few questions to the customers who visit the shopping mall. By analyzing the data that is collected and predicting the number of twowheelers and four-wheelers that will be present on a particular day (weekdays or weekends) at a particular time (Morning, Afternoon, Evening, and Night), the parking area can be divided accordingly based on the vehicles that are more, in that way parking area can be used efficiently. To predict the number of different vehicles machine learning and deep learning techniques can be applied among them the optimal one will be selected and finalized based on the time taken for training and testing, accuracy, and the dataset that is being used. To make it easy and beneficial for the customers in this project a webpage is created that provides a good and easy-to-use interface in which one can easily book slots and clear slots when they wanted to reverse out from the parking spot. This will help in reducing parking space shortages and also helps in avoiding unnecessary conflicts among customers.