Embedded human detection system for home security

Oscar Arturo González González; Alina Mariana Pérez Soberanes; Víctor Hugo García Ortega; Julio César Sosa Savedra

doi:10.1007/978-3-030-62554-2_4

Embedded human detection system for home security

Oscar Arturo González González, Alina Mariana Pérez Soberanes, Víctor Hugo García Ortega, Julio César Sosa Savedra

Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada (CICATA), Unidad Querétaro

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper presents the development of an embedded system prototype that performs the home security monitoring, through image processing and classification algorithms to detect human form. If human presence is detected, the system will send an alert message to the user. The embedded system is implemented on a Raspberry Pi 3 B, supported by a Pyroelectric Infrared Radial (PIR) motion sensor and a Raspberry Pi Camera V2. The algorithms are implemented in C language and were designed to take advantage of the hardware resources of the platform, through High Performance Computing (HPC) techniques. The selected classifier is a multilayer perceptron. This classifier obtained an accuracy of 96%, approximately.

Original language	English
Title of host publication	Telematics and Computing - 9th International Congress, WITCOM 2020, Proceedings
Editors	Miguel Félix Mata-Rivera, Roberto Zagal-Flores, Cristian Barria-Huidobro
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	48-60
Number of pages	13
ISBN (Print)	9783030625535
DOIs	https://doi.org/10.1007/978-3-030-62554-2_4
State	Published - 2020
Event	9th International Congress on Telematics and Computing, WITCOM 2020 - Puerto Vallarta, Mexico Duration: 2 Nov 2020 → 6 Nov 2020

Publication series

Name	Communications in Computer and Information Science
Volume	1280
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	9th International Congress on Telematics and Computing, WITCOM 2020
Country/Territory	Mexico
City	Puerto Vallarta
Period	2/11/20 → 6/11/20

Keywords

Embedded system
HPC
Image processing
Multilayer perceptron
Raspberry Pi

Access to Document

10.1007/978-3-030-62554-2_4

Cite this

González González, O. A., Pérez Soberanes, A. M., García Ortega, V. H., & Sosa Savedra, J. C. (2020). Embedded human detection system for home security. In M. F. Mata-Rivera, R. Zagal-Flores, & C. Barria-Huidobro (Eds.), Telematics and Computing - 9th International Congress, WITCOM 2020, Proceedings (pp. 48-60). (Communications in Computer and Information Science; Vol. 1280). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-62554-2_4

González González, Oscar Arturo ; Pérez Soberanes, Alina Mariana ; García Ortega, Víctor Hugo et al. / Embedded human detection system for home security. Telematics and Computing - 9th International Congress, WITCOM 2020, Proceedings. editor / Miguel Félix Mata-Rivera ; Roberto Zagal-Flores ; Cristian Barria-Huidobro. Springer Science and Business Media Deutschland GmbH, 2020. pp. 48-60 (Communications in Computer and Information Science).

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abstract = "This paper presents the development of an embedded system prototype that performs the home security monitoring, through image processing and classification algorithms to detect human form. If human presence is detected, the system will send an alert message to the user. The embedded system is implemented on a Raspberry Pi 3 B, supported by a Pyroelectric Infrared Radial (PIR) motion sensor and a Raspberry Pi Camera V2. The algorithms are implemented in C language and were designed to take advantage of the hardware resources of the platform, through High Performance Computing (HPC) techniques. The selected classifier is a multilayer perceptron. This classifier obtained an accuracy of 96%, approximately.",

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González González, OA, Pérez Soberanes, AM, García Ortega, VH & Sosa Savedra, JC 2020, Embedded human detection system for home security. in MF Mata-Rivera, R Zagal-Flores & C Barria-Huidobro (eds), Telematics and Computing - 9th International Congress, WITCOM 2020, Proceedings. Communications in Computer and Information Science, vol. 1280, Springer Science and Business Media Deutschland GmbH, pp. 48-60, 9th International Congress on Telematics and Computing, WITCOM 2020, Puerto Vallarta, Mexico, 2/11/20. https://doi.org/10.1007/978-3-030-62554-2_4

Embedded human detection system for home security. / González González, Oscar Arturo; Pérez Soberanes, Alina Mariana; García Ortega, Víctor Hugo et al.
Telematics and Computing - 9th International Congress, WITCOM 2020, Proceedings. ed. / Miguel Félix Mata-Rivera; Roberto Zagal-Flores; Cristian Barria-Huidobro. Springer Science and Business Media Deutschland GmbH, 2020. p. 48-60 (Communications in Computer and Information Science; Vol. 1280).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - García Ortega, Víctor Hugo

AU - Sosa Savedra, Julio César

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AB - This paper presents the development of an embedded system prototype that performs the home security monitoring, through image processing and classification algorithms to detect human form. If human presence is detected, the system will send an alert message to the user. The embedded system is implemented on a Raspberry Pi 3 B, supported by a Pyroelectric Infrared Radial (PIR) motion sensor and a Raspberry Pi Camera V2. The algorithms are implemented in C language and were designed to take advantage of the hardware resources of the platform, through High Performance Computing (HPC) techniques. The selected classifier is a multilayer perceptron. This classifier obtained an accuracy of 96%, approximately.

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González González OA, Pérez Soberanes AM, García Ortega VH, Sosa Savedra JC. Embedded human detection system for home security. In Mata-Rivera MF, Zagal-Flores R, Barria-Huidobro C, editors, Telematics and Computing - 9th International Congress, WITCOM 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 48-60. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-62554-2_4

Embedded human detection system for home security

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