Image Processing and IoT Based Smart Parking Slot Detection and Notification System

An automated parking system improves efficiency by providing real-time space availability, reducing search time and costs. In multi-story lots, drivers often struggle to find open spots due to the lack of direct monitoring and information displays. As urban areas grow and more cars fill the streets, efficient parking solutions become essential. Our research aims to develop a system that simplifies smart parking slot management. The system is powered by a Raspberry Pi, which monitors large-scale operations and performs extensive data analysis. It runs an advanced image processing algorithm YOLOv11 to analyze live video feeds and identify available parking spots. Data is transmitted from the Raspberry Pi to the server using the LoRa communication protocol. After image processing, the data is stored in a MySQL database. An additional improvement to the system includes the ability to handle rotating CCTV images from basement cameras, enhancing its functionality. This system allows users to easily locate open parking spaces via their smartphones through the Blynk app. System reduces the time spent searching for parking and alleviates traffic congestion, making it a scalable and cost-effective solution for urban environments.