scholarly journals An Approach to Smart Home Security System Using Ardunio

2017 ◽  
Vol 4 (2/3) ◽  
pp. 01-18 ◽  
Author(s):  
Abel A. Zandamela
Keyword(s):  
Smart Home ◽  
Security System ◽  
Home Security

Smart Home Security System

2020 ◽  
pp. 127-133
Author(s):  
Vemireddy Sai sindhu reddy ◽  
P. V. K. Sai ◽  
Anupama Namburu
Keyword(s):  
Smart Home ◽  
Security System ◽  
Home Security

i-SHSS: An IoT Based Smart Home Security System

2017 ◽  
pp. 303-306
Author(s):  
Saurabh Singh ◽  
Pradip Kumar Sharma ◽  
Seo Yeon Moon ◽  
Jong Hyuk Park
Keyword(s):  
Smart Home ◽  
Security System ◽  
Home Security

scholarly journals Smart Home Security System using Iot, Face Recognition and Raspberry Pi

2020 ◽  
Vol 176 (13) ◽  
pp. 45-47
Author(s):  
Manoj R. ◽  
Rekha Y. ◽  
Raju R. ◽  
Sharad A.
Keyword(s):  
Face Recognition ◽  
Smart Home ◽  
Security System ◽  
Raspberry Pi ◽  
Home Security

scholarly journals Smart Home Multi-Factor Authentication Using Face Recognition and One-Time Password on Smartphone

2021 ◽  
Vol 15 (24) ◽  
pp. 32-48
Author(s):  
Yen Xin Tok ◽  
Norliza Katuk ◽  
Ahmad Suki Che Mohamed Arif
Keyword(s):  
Smart Home ◽  
Facial Recognition ◽  
Security System ◽  
Primary Concern ◽  
Application Development ◽  
Home Security ◽  
Voice Control ◽  
One Time Password ◽  
Home Technology ◽  
Smart Home Technology

Recently, the adoption of smart home technology has been on the rise and becoming a trend for home residents. The development of Internet-of-Things (IoT) technology drives the smart home authentication system with biometric systems such as facial recognition, fingerprint, and voice control techniques. In the context of homeowners, security is always the primary concern. However, conventional home security and the existing smart home security system have some limitations. These techniques use single-factor authentication, which provides limited protection for home security. Therefore, this project proposed a design for smart home multi-factor authentication using facial recognition and a one-time password sent to smartphones for a home security system. Rapid application development was the methodology for conducting this study. A usability evaluation suggested that the proposed smart home multi-factor authentication is acceptable, but some usability issues can be improved in the future. 

scholarly journals Face recognition system with PCA-GA algorithm for smart home door security using Rasberry Pi

2020 ◽  
Vol 8 (3) ◽  
pp. 210-216
Author(s):  
Subiyanto Subiyanto ◽  
Dina Priliyana ◽  
Moh. Eki Riyadani ◽  
Nur Iksan ◽  
Hari Wibawanto
Keyword(s):  
Face Recognition ◽  
Smart Home ◽  
Principal Component ◽  
Recognition System ◽  
Classification Performance ◽  
Security System ◽  
Raspberry Pi ◽  
Home Security ◽  
Ga Algorithm ◽  
The Face

Genetic algorithm (GA) can improve the classification of the face recognition process in the principal component analysis (PCA). However, the accuracy of this algorithm for the smart home security system has not been further analyzed. This paper presents the accuracy of face recognition using PCA-GA for the smart home security system on Raspberry Pi. PCA was used as the face recognition algorithm, while GA to improve the classification performance of face image search. The PCA-GA algorithm was implemented on the Raspberry Pi. If an authorized person accesses the door of the house, the relay circuit will unlock the door. The accuracy of the system was compared to other face recognition algorithms, namely LBPH-GA and PCA. The results show that PCA-GA face recognition has an accuracy of 90 %, while PCA and LBPH-GA have 80 % and 90 %, respectively.

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