Development of a Vision-Based Smart Security System for Vehicle Entry Monitoring in a Subdivision

Gated subdivisions and villages enhance community security through monitored access points in the Philippines. This study focuses on developing a robust electronic system for vehicle entry monitoring, leveraging machine vision and data analysis. The primary objective is to create an advanced security system that uses cameras to monitor and identify vehicles via their license plates. The system ensures accurate logging and classification of vehicles by integrating Automatic License Plate Recognition (ALPR) technology with an SQL database. Implemented in Sta. Cecilia Village in Las <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{Pinas}$</tex> City, the system achieved a high accuracy rate of 96.83% in vehicle detection and classification. This approach improves security by efficiently tracking vehicle entries and providing valuable traffic analysis data. The results demonstrate the system's potential to enhance community safety and operational efficiency, making it a promising solution for modern urban management.