The research paper aims to address the challenges faced by visitors in finding parking spaces in crowded public areas. The primary objective is to design and implement a smart parking management system that utilizes IoT and web technology to provide real-time information about available parking slots to visitors. The proposed system consists of various modules, including IR sensors for slot monitoring, RFID cards for user authentication, LCD displays for slot information, and a Blynk application for remote access to parking status. The system also incorporates deep learning techniques for vehicle re-identification, enhancing security and preventing car theft. Through extensive literature review and experimentation, the research paper establishes the effectiveness of IoT and web technology in developing a visitor-friendly smart parking system. It demonstrates the successful integration of real-time data, cloud-based services, and user-friendly interfaces to provide a seamless parking experience for visitors. The findings of the research paper highlight the significant improvements in parking efficiency, reduction in time wasted searching for parking spaces, and the convenience provided to both nearby and distant visitors. The deep learning module for vehicle re-identification proves to be effective in enhancing parking security.

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