DESIGN AND IMPLEMENTATION OF AN IOT-BASED ACCESS CONTROL SYSTEM COMBINING AUTOMATIC LICENSE-PLATE RECOGNITION AND RADIO-FREQUENCY IDENTIFICATION TECHNOLOGIES

Nazar Omeliukh, Halyna Klym, Taras Tkachuk

Abstract


Background. Ensuring security for private areas and infrastructure hubs is a growing concern in the modern world. Traditional methods, such as human guards and mechanical barriers operated by physical tokens (keys or cards), are often slow, inefficient, and prone to security risks like unauthorized duplication or theft. Furthermore, legacy systems lack comprehensive auditing capabilities. This creates a critical need for modern, automated IoT-based systems that ensure reliable access management and real-time monitoring.

Materials and Methods. The system uses several electronic components. The core is a low-cost microcontroller with a camera module. A radio-frequency identification (RFID) reader scans access cards. An ultrasonic distance sensor detects obstacles for safety, and a servo motor operates the physical barrier. The software backend was developed in Python, with a JavaScript (React) web control panel.

The system combines two identification methods. First, a camera captures a vehicle's image, sending it to a server where an AI model reads the license plate. The server checks the number against an approved list. If not recognized, the driver scans an RFID card as a secondary method. A distance sensor continuously monitors the barrier area to prevent closing on an obstacle. A web interface allows an operator to monitor the camera, review logs, and manually open the barrier.

Results. The developed system was tested successfully. The AI model achieved 75% accuracy in identifying license plates. The system proved fast, with an average response time from image capture to decision under one second. The safety sensor was validated, reliably detecting obstacles and preventing barrier movement, ensuring safe operation. Provided results of comparing video quality and system response time. The optimal balance between video quality and speed was found at 800x600 resolution.

Conclusions. A reliable, cost-effective automated access control system was successfully designed, built, and tested. The combination of AI-based license plate reading with a backup RFID system provides a robust, flexible solution. This system is well-suited for improving security and efficiency in real-world applications like residential, office, and industrial zones.

Keywords: automated access control, ESP32-S3, ALPR, RFID, security.


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References


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DOI: http://dx.doi.org/10.30970/eli.32.9

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