Intruder Detection System Using Face Recognition for Home Security IoT Applications: A Python Raspberry Pi 3 Case Study

2018 ◽  
Vol 5 (2) ◽  
pp. 21-32 ◽  
Author(s):  
Ramanpreet Kaur Deol ◽  
Keyword(s):  
Face Recognition ◽  
Detection System ◽  
Raspberry Pi ◽  
Iot Applications ◽  
Home Security ◽  
Intruder Detection

Face recognition in an intelligent door lock with ResNet model based on deep learning

2021 ◽  
pp. 1-11
Author(s):  
Suphawimon Phawinee ◽  
Jing-Fang Cai ◽  
Zhe-Yu Guo ◽  
Hao-Ze Zheng ◽  
Guan-Chen Chen
Keyword(s):  
Face Recognition ◽  
Detection System ◽  
Low Cost ◽  
Ease Of Use ◽  
Raspberry Pi ◽  
Training Methods ◽  
Graphics Recognition ◽  
Face Images ◽  
The Face ◽  
Door Lock

Internet of Things is considerably increasing the levels of convenience at homes. The smart door lock is an entry product for smart homes. This work used Raspberry Pi, because of its low cost, as the main control board to apply face recognition technology to a door lock. The installation of the control sensing module with the GPIO expansion function of Raspberry Pi also improved the antitheft mechanism of the door lock. For ease of use, a mobile application (hereafter, app) was developed for users to upload their face images for processing. The app sends the images to Firebase and then the program downloads the images and captures the face as a training set. The face detection system was designed on the basis of machine learning and equipped with a Haar built-in OpenCV graphics recognition program. The system used four training methods: convolutional neural network, VGG-16, VGG-19, and ResNet50. After the training process, the program could recognize the user’s face to open the door lock. A prototype was constructed that could control the door lock and the antitheft system and stream real-time images from the camera to the app.

Acoustic intruder detection system for home security

2005 ◽  
Vol 51 (1) ◽  
pp. 130-138 ◽  
Author(s):  
Young-Keun Choi ◽  
Ki-Man Kim ◽  
Ji-Won Jung ◽  
Seung-Yong Chun ◽  
Kyu-Sik Park
Keyword(s):  
Detection System ◽  
Home Security ◽  
Intruder Detection

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 INTERNET OF THINGS (IOT) BASED ADVANCED ONLINE EXAMINATION USING RASPBERRY PI

2020 ◽  
Vol 5 (5) ◽  
pp. 26-32
Author(s):  
Kunal Pawar ◽  
Pravin Latane
Keyword(s):  
Face Recognition ◽  
Internet Of Things ◽  
Raspberry Pi ◽  
Alarm System ◽  
Iot Applications ◽  
System A ◽  
Implementation Techniques ◽  
Online Examination ◽  
On Line ◽  
Exam System

In this research we have proposed IOT based advanced Online examination using Raspberry pi for Alarm system and border security. With the event of recent education, considering the defect of current online exam system, a replacement projection of online exam system primarily based on Raspberry pi IOT is projected, and also the key implementation techniques and ways also are represented. Internet of Things (IOT) has provided a promising chance to make powerful Examination systems and applications by leverage the growing omnipresence of wireless, RFID mobile and detector devices. a large vary of IOT applications are developed in recent years. In a shot to grasp the event of IOT in on-line examination, here we tend to propose this analysis of IOT, IOT key facultative technologies, major IOT applications in on-line examination and identifies analysis trends and challenges. Here we tend to introduce all the examiner details square measure holds on within the server. Then if somebody needs to starts on-line examination, 1st they ought to apply face recognition (in Open CV based) technique. as a result of it slow unwanted person conjointly enter to Wright the examination, thus this can be the simplest thanks to known any culprits square measure found or not. Then examination enter to Wright the exam, here conjointly I am apply some security. Currently a day’s already queries square measure hold on within the on-line or any paper written copy.

scholarly journals IoT based facial recognition door access control home security system using raspberry pi

2020 ◽  
Vol 11 (1) ◽  
pp. 417
Author(s):  
Syafeeza Ahmad Radzi ◽  
M.K. Mohd Fitri Alif ◽  
Y. Nursyifaa Athirah ◽  
A. S. Jaafar ◽  
A. H. Norihan ◽  
...  
Keyword(s):  
Face Recognition ◽  
Access Control ◽  
Security System ◽  
Raspberry Pi ◽  
Small Computer ◽  
Home Security ◽  
Learning Technique ◽  
Access Control System ◽  
Computer Board ◽  
Internet Of Thing

The home security system has become vital for every house. Previously, most doors can be open by using traditional ways, such as keys, security cards, password or pattern. However, incidents such as a key loss has led to much worrying cases such as robbery and identity fraud. This has become a significant issue. To overcome this problem, face recognition using deep learning technique was introduced and Internet of Thing (IoT) also been used to perform efficient door access control system. Raspberry Pi is a programmable small computer board and used as the main controller for face recognition, youth system and locking system. The camera is used to capture images of the person in front of the door. IoT system enables the user to control the door access.

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.

Intruder Detection System Through Walking Pattern Analysis for Home Security

2021 ◽  
Author(s):  
R.C.P.D. Peiris ◽  
R. Tharmikka ◽  
H.M.V.R. Herath ◽  
M.B. Dissanayake ◽  
U.S. Navaratne
Keyword(s):  
Pattern Analysis ◽  
Detection System ◽  
Home Security ◽  
Walking Pattern ◽  
Intruder Detection

IoT Applications in Smart Home Security

2021 ◽  
pp. 251-277
Author(s):  
Rohit Rastogi ◽  
Rishabh Jain ◽  
Puru Jain
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Smart Home ◽  
Detection System ◽  
Piezoelectric Sensors ◽  
Home Automation ◽  
State Security ◽  
Iot Applications ◽  
Home Security ◽  
High Security

Robotization has changed into a fundamental piece of our lives. Everybody is completely subject to mechanization whether it is an extraordinary bundling or home robotization. So as to bring home automation into thought, everybody now needs a heterogeneous state security, and in our task on residential robotization, such high security highlights are completely on the best possible consumption. Piezoelectric sensors are compelling for sharpening appropriated wellbeing checking and structures. An intrusion detection system (IDS) is a structure that screens for suspicious movement and issues alarms when such advancement is found. Some obstruction divulgence structures are fit to take practice when poisonous improvement or peculiar action is perceived.

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