IRO Journals
Journal of Information Technology and Digital World

Design and Implementation of a Secure Autonomous Indoor Delivery Robot Using Deep Learning-Based Face Recognition

Open Access
Published: 18 May, 2026
Pages: 101-115
  • Malleshwari M. , Malleshwari M.
    Student, Department of Electronics and Communication Engineering, P.S.V College of Engineering and Technology, Krishnagiri, India
    Student, Department of Electronics and Communication Engineering, P.S.V College of Engineering and Technology, Krishnagiri, India
  • Mamtha G. , Mamtha G.
    Student, Department of Electronics and Communication Engineering, P.S.V College of Engineering and Technology, Krishnagiri, India
    Student, Department of Electronics and Communication Engineering, P.S.V College of Engineering and Technology, Krishnagiri, India
  • Nisha R. , Nisha R.
    Student, Department of Electronics and Communication Engineering, P.S.V College of Engineering and Technology, Krishnagiri, India
    Student, Department of Electronics and Communication Engineering, P.S.V College of Engineering and Technology, Krishnagiri, India
  • Nandhini M. Nandhini M.
    Professor, Department of Electronics and Communication Engineering, P.S.V College of Engineering and Technology, Krishnagiri, India
    Professor, Department of Electronics and Communication Engineering, P.S.V College of Engineering and Technology, Krishnagiri, India
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How to Cite

M., Malleshwari, Mamtha G., Nisha R., and Nandhini M. 2026. “Design and Implementation of a Secure Autonomous Indoor Delivery Robot Using Deep Learning-Based Face Recognition”. Journal of Information Technology and Digital World 8 (2): 101-15. https://doi.org/10.36548/jitdw.2026.2.003.
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Keywords

Autonomous Indoor Delivery Robot
Deep Learning
Face Recognition
Deep Neural Network (DNN)
ESP32
Internet of Things (IoT)
Secure Delivery
Smart Robotics

Abstract

This paper discusses the development and implementation of an indoor delivery robot equipped with the face recognition facility through a deep learning-based architecture for authentic and safe delivery within smart indoor locations. This system will provide benefits in terms of enhanced security, automation, and efficiency for purposes like delivering items in hospitals, offices, laboratory areas, and smart indoor buildings. The face recognition facility will be implemented through a Deep Neural Network (DNN) approach for recognizing the user for verification. A robot platform is created through an ESP32 microcontroller connected to DC motors, motor driver, camera module, and ultrasonic sensors. The proposed robot will be able to move in designated areas inside the smart environment while detecting any possible obstruction in its way. Once the robot reaches the destination point, it will use the face recognition facility for authenticating the user before giving access to the package. Furthermore, communication over the Internet of Things (IoT) platform facilitates wireless monitoring and management. Experimental analysis indicates robust navigational skills and reliable obstacle detection.

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