Development of Face Recognition on Raspberry Pi for Security Enhancement of Smart Home System

Gunawan, Teddy Surya; Gani, Muhammad Hamdan Hasan; Rahman, Farah Diyana Abdul; Kartiwi, Mira

doi:10.11591/ijeei.v5i4.361

Cited by 29 publications

(12 citation statements)

References 10 publications

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“…Perangkat seperti keamanan rumah pintar ini sangat diperlukan dalam kehidupan sehari-hari [3]. Salah satu aspek keamanan rumah pintar adalah kunci pintu rumah agar dapat membuka dan mengunci seclara otomatis [4].…”

Section: Pendahuluanunclassified

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

Subiyanto

Priliyana

Riyadani

et al. 2020

Jurnal Teknologi dan Sistem Komputer

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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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Section: Pendahuluanunclassified

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

Subiyanto

Priliyana

Riyadani

et al. 2020

Jurnal Teknologi dan Sistem Komputer

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“…Este dispositivo ha sido utilizado en distintos proyectos tecnológicos y de desarrollo, tales como sistemas de seguridad basados en la detección de rostros [5], o sistemas de alarmas que envía videos y fotografías cuando un movimiento es detectado en el inmueble a proteger [6].…”

Section: Raspberry Piunclassified

Diseño de una red neuronal distribuida entre dispositivos Raspberry Pi conectados a Internet por medio de XMPP

Contreras¹,

Varela²,

Gudiño-Peñaloza³

2019

RCS

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Resumen. Actualmente se tienen diferentes esquemas de comunicación que buscan la interconexión de la mayor cantidad de dispositivos posibles, tal como el Internet de las Cosas, para así poder controlar actuadores u obtener datos desde diferentes puntos geográficos. Cuando se tienen situaciones tales como el estudio de los comportamientos ambientales, análisis de los comportamientos de consumo de individuos, o análisis de comportamientos poblacionales generales, es necesario obtener información de diferentes zonas y analizarlas en conjunto para obtener el resultado adecuado. Por este motivo, la generación de sistemas que puedan trabajar en conjunto desde distintas latitudes se vuelve un tema de estudio importante. En este trabajo se describirán diferentes modelos para la generación de una red neuronal distribuida, o segmentada, entre diferentes dispositivos conectados a Internet comunicándose mediante el protocolo de mensajería XMPP. Estos modelos logran identificar patrones de entrenamiento con datos provenientes desde distintas fuentes. El modelo utiliza tarjetas de desarrollo Raspberry Pi 3B+ para procesar y entrenar la red neuronal.Palabras clave: internet de las cosas, redes neuronales distribuidas, cómputo distribuido, Raspberry Pi, XM PP.Abstract. Currently there are different communication schemes that seek the interconnection of any kind of devices, such as the Internet of Things, in order to control actuators or obtain data from different geographical points. When there are situations such as the study of environmental behaviors, or analysis of general population behaviors, it is necessary to obtain information from different areas and analyze such data together to obtain the correct result. For this reason, the generation of systems that can work together from different latitudes becomes an important topic of study. In this paper we will describe different models for the generation of a distributed or segmented neural network between different de-197

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“…The authors of [9] proposed a face recognition security system using Raspberry Pi which can be connected to the smart home system. Eigenface was used the feature extraction, while Principal Component Analysis (PCA) was used as the classifier.…”

Section: Related Workmentioning

confidence: 99%

A new approach to gather similar operations extracted from web services

Sara¹,

Bakhta²,

Loukil³

2019

IJECE

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<span lang="EN-US">A web service is an autonomous software that exposes a set of features on the Internet, it is developed and published by providers and accessed by customers who discover it, select it, invoke and use it. Several research policies have been implemented such as searching through keywords, searching according to semantics and searching by estimating the similarity. A customer is looking for a service for the operations he/she carries out, hence the interest of guiding the search for services towards a search for operations: finding the desired operations amounts to finding the services. For this, groupings of similar operations would make it possible to obtain all the services that can meet the desired functionalities. The customer can then select, in this set the service or services according to its non-functional criteria. The paper presents a study of the similarity between operations. The proposed approach is validated through an experimental study conducted on web services belonging to various domains.</span>

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Development of Face Recognition on Raspberry Pi for Security Enhancement of Smart Home System

Cited by 29 publications

References 10 publications

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

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

Diseño de una red neuronal distribuida entre dispositivos Raspberry Pi conectados a Internet por medio de XMPP

A new approach to gather similar operations extracted from web services

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