Design and Implementation of a Single-Gate Parking Barrier Prototype using ESP32-CAM Based on the Internet of Things

Abstract

The rapid proliferation of motorized vehicles within educational institutions necessitates robust parking management infrastructures to mitigate the unauthorized utilization of reserved spaces. This study proposes the design and implementation of an automated, Internet of Things (IoT)-based parking barrier prototype, employing an ESP32-CAM microcontroller as the core computing unit. The primary objective is to restrict facility access exclusively to authorized personnel by automating license plate identification and cross-referencing this telemetry with a cloud database. Unlike conventional edge-heavy systems, this architecture offloads Optical Character Recognition (OCR) processing to a cloud API to reduce thermal throttling and hardware latency on the ESP32-CAM. The methodology integrates an HY-SRF05 ultrasonic sensor for vehicle proximity detection, the ESP32-CAM for optical image acquisition, and a micro servo motor for barrier actuation. Upon detecting a vehicle within a 50 cm threshold, the system autonomously captures the license plate, processes the image via a cloud-based License Plate Recognition (LPR) API, and verifies the extracted string against a Firebase Realtime Database. Empirical testing demonstrated high system reliability; the ultrasonic sensor exhibited a spatial error margin of less than 2 cm, and the integrated IoT communication architecture achieved an operational latency of merely 2 to 3 seconds.