AUTOMATED ACCESS CONTROL SYSTEM FOR A SMART HOUSE USING RASPBERRY PI AND AUTOMATIC NUMBER-PLATE RECOGNITION

Marko Tabachyshyn, Danylo Tabachyshyn, Nataliia Kunanets, Andrii Spitzer

Abstract


Introduction. The article is devoted to the development of an access automation system for a smart home based on a Raspberry Pi 4 single-board computer, ESP32 microcontrollers, a Raspberry Pi Camera Module V2, the YOLOv8 computer vision model (for license plate recognition), and Radio-frequency identification (RFID). The relevance of the study is determined by the need to enhance the security level of smart home systems through the implementation of autonomous access control mechanisms. An analysis of existing solutions and approaches in the field of automated access control and smart home systems was conducted.

Materials and Methods. An architecture of a software and hardware access control system is proposed, which integrates license plate recognition based on the YOLOv8 model and the Tesseract OCR system, RFID authentication, and PIN-based access. MQTT protocol is used for data exchange between system components, while monitoring and control are implemented via a Python microframework Flask-based web interface. Algorithms for automatic gate and door opening, event logging, and management of authorized users and vehicle lists were developed. Experimental evaluation of the system was conducted under static and dynamic conditions.

Results. As a result of the study, an access control system for a smart home supporting Automatic number-plate recognition (ANPR), RFID, and PIN authentication technologies was implemented. Experimental evaluation showed a license plate recognition accuracy of 94% in the intended static operating mode and 50% in the supplementary dynamic stress test. The results obtained confirm the good functionality of the proposed architecture and its applicability for automated access control in a smart home.

Conclusions. It has been established that the use of local data processing based on Raspberry Pi ensures system autonomy and reduces dependence on external services. The practical contribution of the work lies in the development of a low-cost, open, and locally operated access control system integrating ANPR, RFID, and PIN-based authentication for private residential use.

Keywords: smart home, access control system, Raspberry Pi 4, YOLOv8, MQTT, ANPR.


Full Text:

PDF

References


[1] Jiang, R. (2025). The smart home control system based on Raspberry Pi. Journal of Research in Science and Engineering, 7(9), 21–25. https://doi.org/10.53469/jrse.2025.07(09).04

[2] Ramadhan, M., & Yendri, D. (2025). A door lock security system with remote keyless feature using the PUF approach method. CHIPSET, 6, 103–116. https://doi.org/10.25077/chipset.6.02.103-116.2025

[3] Sayeduzzaman, M., Hasan, T., Nasser, A., & Negi, A. (2023). An Internet of Things‐integrated home automation with smart security system. https://doi.org/10.1002/9781394213948.ch13

[4] Garba, A., As, I., & Baballe, M. (2024). Design of an ESP32-based IoT smart home automation management system. Zenodo.
https://doi.org/10.5281/zenodo.13334218

[5] Aramice, G. A. (2017). Smart House Two Level Security System. Journal of Al-Turath University College, 23, 15–25. https://www.researchgate.net/publication/319182193_Smart_House_Two_Level_Security_System

[6] Google. (n.d.). Google Nest smart home devices. https://store.google.com/category/connected_home

[7] Xiaomi. (n.d.). Mi Home IoT privacy white paper. https://trust.mi.com/docs/iot-privacy-white-paper-global/3/6

[8] Hikvision. (2024). Vehicle access control management.
https://www.hikvision.com

[9] Milesight. (2026). Edge AI-powered ANPR access control: Faster, smoother, and more precise vehicle access.
https://www.milesight.com

[10] Ajax Systems. (n.d.). Products and integrations ecosystem.
https://ajax.systems

[11] Espressif Systems. (n.d.). ESP32 series datasheet. https://www.espressif.com/sites/default/files/documentation/esp32_datasheet_en.pdf

[12] Raspberry Pi Foundation. (n.d.). Raspberry Pi 4 Model B. https://www.raspberrypi.org/products/raspberry-pi-4-model-b/

[13] Raspberry Pi Foundation. (n.d.). Raspberry Pi Camera Module V2. https://www.raspberrypi.org/products/camera-module-v2/

[14] Components101. (n.d.). HC-SR501 PIR sensor datasheet. https://components101.com/sites/default/files/component_datasheet/HC%20SR501%20PIR%20Sensor%20Datasheet.pdf

[15] SparkFun Electronics. (n.d.). 4x4 matrix keypad datasheet. https://cdn.sparkfun.com/assets/f/f/a/5/0/DS-16038.pdf

[16] Handson Technology. (n.d.). RFID-RC522 datasheet. https://www.handsontec.com/dataspecs/RC522.pdf

[17] Mouser Electronics. (n.d.). 28BYJ-48 stepper motor datasheet. https://www.mouser.com/datasheet/2/758/stepd-01-data-sheet-1143075.pdf

[18] STMicroelectronics. (n.d.). ULN2001A/ULN2003A high-voltage, high-current Darlington transistor arrays.
https://www.st.com/resource/en/datasheet/uln2001.pdf

[19] Forter. (n.d.). CoVi Security MC-21 Brown door sensor. https://www.forter.com.ua/datchik-vdkrittya-dvereyvkon-covi-security-mc-21-brown/

[20] Vishay Intertechnology. (n.d.). LCD 16x2 character display (LCD016N002BCFHET) datasheet.
https://www.vishay.com/docs/37484/lcd016n002bcfhet.pdf

[21] Tesseract OCR. (n.d.). Tesseract OCR engine. GitHub.
https://github.com/tesseract-ocr/tesseract

[22] Tower Pro. (n.d.). SG90 servo motor datasheet. http://www.ee.ic.ac.uk/pcheung/teaching/DE1_EE/stores/sg90_datasheet.pdf

[23] Ultralytics. (2024). YOLOv8 documentation. https://docs.ultralytics.com/models/yolov8/




DOI: http://dx.doi.org/10.30970/eli.35.11

Refbacks

  • There are currently no refbacks.