IoT Enabled Smart Security Framework for 3D Printed Smart Home

Xu, Z., Ansari, S. , Abdulghani, A. M., Imran, M. A. and Abbasi, Q. (2020) IoT Enabled Smart Security Framework for 3D Printed Smart Home. In: IEEE SmartIoT 2020, Beijing, China, 14-16 Aug 2020, ISBN 9781728165141 (doi: 10.1109/SmartIoT49966.2020.00026)

Abstract

Recently, smart home design using Internet of Things (IoT) technology has become a growing industry. Since security is the most important element of the smart home design, the project aims to design a 3D printed smart home with a focus on the security features that would meet the security design of futuristic real homes. The surveillance system of traditional smart home is separated from the door lock system. This project innovatively integrates and coordinates them through the facial recognition algorithms, which forms the entry system of this design. The overall system can be divided into two subsystems (parts), which are the sensing and actuation system (PART I) and the entry system (PART II). PART I includes various sensors and actuators to ensure the security of home, including combustible gas sensor, air quality sensor and temperature & humidity sensor. When anomalies are detected by sensors, actuators such as ventilator, buzzer and LEDs start to work. In PART II, the PIR motion sensor is utilized to detect the person to activate the facial recognition step. Facial recognition algorithm (LBPH algorithm) is implemented for person classification, which is used in selecting the duration of recording for the surveillance system. The surveillance system could select not to record for the occupants or different levels of recording for each occupant based on the confidence of recognition. The project outcomes a 3D printed smart home with a door lock system, a surveillance system, and a sensing & actuation network, which accomplishes the security features in perception and network layer of IoT system design.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Ansari, Dr Shuja and Imran, Professor Muhammad and Abbasi, Professor Qammer and Abdulghani, Dr Amir Mohamed
• Authors: Xu, Z., Ansari, S., Abdulghani, A. M., Imran, M. A., and Abbasi, Q.
• College/School: College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering; College of Science and Engineering > School of Engineering > Systems Power and Energy
• ISBN: 9781728165141
• Copyright Holders: Copyright © 2020 IEEE
• First Published: First published in 2020 IEEE International Conference on Smart Internet of Things (SmartIoT)
• Publisher Policy: Reproduced in accordance with the publisher copyright policy

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