Smart Parking System using QR Code

This project presents the development and implementation of an advanced Parking Management System, designed to address the growing challenges of efficient parking space allocation and management in urban environments. The system aims to streamline parking operations for both administrators and users, offering a comprehensive solution that leverages modern technologies. The core of the system comprises two primary components: a robust administrator panel developed using Laravel 8.83, and a user-friendly mobile application built with Flutter 2.2. The Laravel-based admin panel provides a centralized interface for managing parking resources, including adding, editing, and deleting parking slots, managing user accounts, generating reports, and configuring dynamic pricing rules. The Flutter mobile application enables users to easily search for nearby parking locations based on their current location (obtained using the geolocator package and Google Maps API), view real-time slot availability, book parking slots, and manage their bookings. A key feature of the system is the implementation of dynamic pricing, which adjusts parking fees based on demand and availability. This algorithm, implemented in Laravel using the Pricing Controller, considers factors such as the percentage of occupied slots and the time of day to determine optimal pricing strategies. Another important aspect of the system is secure access control, achieved through the generation and validation of QR codes. Each booking is associated with a unique QR code, which is generated using the qr_flutter package in the mobile app and validated by the administrator using the qr_code_scanner package. The system utilizes RESTful APIs secured with Laravel Sanctum for authentication, ensuring secure and efficient data exchange between the Flutter app and the Laravel backend. The database, implemented in MySQL 8.0.26, stores information about users, parking slots, bookings, and pricing rules. Extensive testing was conducted to validate the system's functionality, performance, and security. Testing results indicate that the system effectively manages parking resources, reducing manual effort by an estimated 70% (based on time studies conducted at [Testing Location]) and providing a user-friendly experience with an average booking completion time of under 60 seconds. The dynamic pricing algorithm resulted in a 15% increase in parking revenue during peak hours, demonstrating its effectiveness in optimizing parking utilization. The system is a viable solution for improving parking management efficiency and enhancing the overall parking experience for both operators and users..