Enhanced economy based smart parking system using Machine Learning

Abstract

For the development of smart cities, various types of smart applications are requisite vise smart health care, smart electricity system, smart home, smart parking system, smart irrigation, and smart waste management system, etc. In these applications, the smart parking system is one of the most important aspects of a smart city. But finding the parking space in a very large parking area has been becoming a serious problem because of increase in the number of vehicles on the road and the number of fewer parking slots available for parking. The drivers are wasting so much time and fuel to find the proper parking slots.

The proposed work applies Linear Regression approach of Machine Learning for forecasting and predicting future parking price changes based upon the previous dataset. The user can change the parking price according to his needs. Also, it describes varied factors which directly or indirectly affects parking price.

Using the proposed system, users can view the available slots and book slots based upon their choices of place, pricing option, etc. This web system assists the customer to book parking spaces online. User can pay the parking charges online through PayPal account. Hence this application reduces the user’s effort and time of searching the parking space and also avoids the congestion of traffic.