ASPS - AI-Driven Smart Parking Solutions with Integrated Web and Mobile Applications

The research suggests a smart parking system using the combination of AIoT and Edge Computing, in there, Raspberry Pi
collects the data from cameras and sensors and then transfers it to the local computer for AI to process and overcome the
performance limitations of the Raspberry Pi and create the comprehensive parking system including the website for admin
and mobile application for users. Previous research on smart parking systems has evolved both simple solutions using
sensors to advanced systems that integrate AI and cameras (dual cameras system with 96.74% accuracy and fisheye camera
system with YOLOv5 reached 94.3%), however, there are still some restrictions covering brightness, weather conditions,
etc. The key features include license plate detection using YOLOv10, displaying superior results than others. This smart
parking system solves the existing issues by leveraging edge computing to handle these AI tasks. Data collected from
cameras and sensors will be processed locally, ensuring real-time performance. The web platform allows remote
management, while the mobile app provides detailed information about the driver and also the online payment function.
Future enhancements cover the slot reservation function and AI-powered available space detection besides other factors
such as reducing traffic congestion, improving parking management, and decreasing pollution. The project will offer a
scalable solution for urban areas with high demand for vehicles like Ho Chi Minh City combined with low-cost
hardware/sensors and advanced AI models, from there can contribute to the development of a smart city with efficient and
user-friendly smart parking system.