A Deep Learning and IoT-Based Smart Access Control System Using Facial Biometrics andTelegram-Assisted Remote Authentication

Authors

  • Yathish N A Dept. of Studies in Computer Science, Davangere University, Davangere, India.
  • Chandrakanth Naikodi Dept. of Studies in Computer Science, Davangere University, Davanagere, India.
  • Sushma B Malipatil Department of Computer Science & Engineering, Vijaya Vittala Institute of Technology.
  • Venkappanavara Basavaraja Department of Studies in Computer Science, Davangere University- 577007 India.

DOI:

https://doi.org/10.70917/ijcisim-2026-5634

Keywords:

Face Recognition, Raspberry Pi, ESP32, Telegram Bot, IoT Security, Smart Door Lock

Abstract

The security systems in smart homes are changing quickly and incorporating Internet of Things (IoT) technologies and biometric authentication capabilities. Smart home security systems are quickly evolving and becoming more sophisticated, including with the introduction of Internet of Things (IoT) technologies and biometric authentication capabilities. In this paper, a smart door unlocking system is presented which unlocks the door automatically by using face recognition through raspberry Pi 4 and the ESP32 NodeMCU module integrated with Telegram chatbot for the of remote door unlock and notifications of the visitor. Using OpenCV and CNN(Resnet) algorithm, the system detects and recognizes face. In the case of an unknown person appearing on the camera, the photo of that person is sent to the owner via Telegram for identification. While using the chatbot, the user can enter unlocking commands that unlock the door remotely. The experiment conducted revealed an accuracy of around 96-99% for the recognition process, attained with low latency. The envisioned system provides a dependable and inexpensive smart security for residences and workplaces.

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Published

2026-09-04

How to Cite

Yathish N A, Chandrakanth Naikodi, Sushma B Malipatil, & Venkappanavara Basavaraja. (2026). A Deep Learning and IoT-Based Smart Access Control System Using Facial Biometrics andTelegram-Assisted Remote Authentication. International Journal of Computer Information Systems and Industrial Management Applications, 18(23s), 709–721. https://doi.org/10.70917/ijcisim-2026-5634

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Section

Original Articles