Smart Parking Application Using Deep Learning Framework

Abstract

Smart parking application is comprised by using Python and Deep Learning Frameworks (DLF). It provides an efficient way of improving the monitoring systems and make use of the data provided by them. By using this system, it is possible to reduce the vital information loss by the operator handling and thus reduce the human processed systems. Images are monitor through the monitoring systems and image processing technique, the data is handled by the Artificial Intelligence (AI) system and then a deciding is generated. This generated Deciding is passed with an image and vehicle information to proper personnel. Now a days, Deep Learning (DL) and AI systems are deployed for automating human handled process using AI and Hardware Integration. The Systems are able to make decisions in various environments and conditions above all affecting factors similar to intelligence expressed by human beings. The decisions made by the systems using deep learning and artificial intelligence methods can even make decisions superior to human intelligence. Integrating the methods of image processing and AI to automate the manned systems in the manner of scaling for any automated systems helps in removing the third-party operators from the control of informant and action. Our proposed idea was reduces the duration of information gathering and deciding of the operator to the information provided and increases the chance of positive results in terms of machine automated results.