Sistema de controle e gerenciamento de acesso
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Tipo de documento: | Trabalho de conclusão de curso |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFAM |
Texto Completo: | http://riu.ufam.edu.br/handle/prefix/6638 |
Resumo: | Technological advances have allowed for the development of increasingly advanced physical access control systems, including electronic devices such as password systems, RFID, and biometrics. Among the most popular biometric systems are facial recognition and fingerprinting, which compare an individual’s biometric characteristics with data previously stored in a database. This paper proposes the creation of an access control and management system that integrates different technologies, including electronic passwords, RFID tags, and facial recognition. In addition, the development of a web-based data management system is proposed. The work was developed using the Raspberry Pi 2 model b, MFRC552 RFID module, 4X4 matrix keypad, camera, button, MariaDB for database management, programming languages Python, HTML, CSS, and PHP, and technologies such as Google Colab. The developed modules function independently and communicate through a socket API. The facial recognition module was validated using Google Colab and was developed using the Long Short Term Memory (LSTM) neural network, achieving an accuracy of 97.04%. After the processes were created, it was necessary to integrate the technologies. Unfortunately, due to hardware limitations, it was not possible to implement facial recognition verification. However, the necessary machine learning algorithms and models for facial recognition were developed and tested on a computer using the MOBIO database. The final system includes password and RFID tag entry options, and despite this limitation, the obtained results were satisfactory, allowing access control only for registered individuals. |
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Sistema de controle e gerenciamento de acessoControle de acessoAutenticaçãoBiometriaENGENHARIASIdentificação biométricaSistemas de segurançaTechnological advances have allowed for the development of increasingly advanced physical access control systems, including electronic devices such as password systems, RFID, and biometrics. Among the most popular biometric systems are facial recognition and fingerprinting, which compare an individual’s biometric characteristics with data previously stored in a database. This paper proposes the creation of an access control and management system that integrates different technologies, including electronic passwords, RFID tags, and facial recognition. In addition, the development of a web-based data management system is proposed. The work was developed using the Raspberry Pi 2 model b, MFRC552 RFID module, 4X4 matrix keypad, camera, button, MariaDB for database management, programming languages Python, HTML, CSS, and PHP, and technologies such as Google Colab. The developed modules function independently and communicate through a socket API. The facial recognition module was validated using Google Colab and was developed using the Long Short Term Memory (LSTM) neural network, achieving an accuracy of 97.04%. After the processes were created, it was necessary to integrate the technologies. Unfortunately, due to hardware limitations, it was not possible to implement facial recognition verification. However, the necessary machine learning algorithms and models for facial recognition were developed and tested on a computer using the MOBIO database. The final system includes password and RFID tag entry options, and despite this limitation, the obtained results were satisfactory, allowing access control only for registered individuals.O avanço tecnológico tem permitido o desenvolvimento de sistemas de controle de acesso físico cada vez mais avançados, incluindo dispositivos eletrônicos como sistemas de senha, RFID e biométricos. Dentre os sistemas biométricos mais populares, destacam-se os de reconhecimento facial e impressão digital, que comparam as características biométricas de um indivíduo com dados previamente cadastrados em um banco de dados. Este trabalho propõe a criação de um sistema de controle e gerenciamento de acesso que integra diferentes tecnologias, sendo estas, senhas eletrônicas, etiquetas RFID e reconhecimento facial. Além disso, é proposto o desenvolvimento de um sistema web para gerenciamento de dados. O trabalho foi desenvolvido utilizando o Raspberry Pi 2 model b, módulo RFID MFRC552, teclado matricial 4X4, câmera, botão, MariaDB para gerenciamento de banco de dados, linguagens de programação Python, HTML, CSS e PHP, e tecnologias como o Google Colab. Os módulos desenvolvidos funcionam de maneira independente e se comunicam através de uma API socket. O módulo de reconhecimento facial foi validado usando o Google Colab e seu desenvolvimento ocorreu através da rede neural Long Short Term Memory (LSTM), obtendo uma acurácia de 97.04%. Após a criação dos processos, foi necessário integrar as tecnologias. Infelizmente, devido a limitações de hardware, não foi possível implementar a verificação por reconhecimento facial. No entanto, os algoritmos e modelo de Machine Learning necessários para o reconhecimento facial foram desenvolvidos e testados em um computador usando a base de dados MOBIO. O sistema final inclui opções de entrada por senha e etiqueta RFID, e apesar dessa limitação, os resultados obtidos foram satisfatórios, permitindo o controle de acesso apenas para pessoas cadastradas.2NãoBrasilFT - Faculdade de TecnologiaManaus (AM)Engenharia Elétrica – Eletrônica - Bacharelado - ManausCosta Filho, Cícero Ferreira Fernandeshttp://lattes.cnpq.br/3029011770761387Costa, Marly Guimarães FernandesCarvalho, Celso BarbosaFigueira, David Laureano dos Santos2023-05-24T15:13:17Z2023-05-24T15:13:17Z2023-02-24info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bachelorThesishttp://riu.ufam.edu.br/handle/prefix/6638porinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFAMinstname:Universidade Federal do Amazonas (UFAM)instacron:UFAM2023-05-24T15:14:17Zoai:localhost:prefix/6638Repositório InstitucionalPUBhttp://riu.ufam.edu.br/oai/requestopendoar:2023-05-24T15:14:17Repositório Institucional da UFAM - Universidade Federal do Amazonas (UFAM)false |
dc.title.none.fl_str_mv |
Sistema de controle e gerenciamento de acesso |
title |
Sistema de controle e gerenciamento de acesso |
spellingShingle |
Sistema de controle e gerenciamento de acesso Figueira, David Laureano dos Santos Controle de acesso Autenticação Biometria ENGENHARIAS Identificação biométrica Sistemas de segurança |
title_short |
Sistema de controle e gerenciamento de acesso |
title_full |
Sistema de controle e gerenciamento de acesso |
title_fullStr |
Sistema de controle e gerenciamento de acesso |
title_full_unstemmed |
Sistema de controle e gerenciamento de acesso |
title_sort |
Sistema de controle e gerenciamento de acesso |
author |
Figueira, David Laureano dos Santos |
author_facet |
Figueira, David Laureano dos Santos |
author_role |
author |
dc.contributor.none.fl_str_mv |
Costa Filho, Cícero Ferreira Fernandes http://lattes.cnpq.br/3029011770761387 Costa, Marly Guimarães Fernandes Carvalho, Celso Barbosa |
dc.contributor.author.fl_str_mv |
Figueira, David Laureano dos Santos |
dc.subject.por.fl_str_mv |
Controle de acesso Autenticação Biometria ENGENHARIAS Identificação biométrica Sistemas de segurança |
topic |
Controle de acesso Autenticação Biometria ENGENHARIAS Identificação biométrica Sistemas de segurança |
description |
Technological advances have allowed for the development of increasingly advanced physical access control systems, including electronic devices such as password systems, RFID, and biometrics. Among the most popular biometric systems are facial recognition and fingerprinting, which compare an individual’s biometric characteristics with data previously stored in a database. This paper proposes the creation of an access control and management system that integrates different technologies, including electronic passwords, RFID tags, and facial recognition. In addition, the development of a web-based data management system is proposed. The work was developed using the Raspberry Pi 2 model b, MFRC552 RFID module, 4X4 matrix keypad, camera, button, MariaDB for database management, programming languages Python, HTML, CSS, and PHP, and technologies such as Google Colab. The developed modules function independently and communicate through a socket API. The facial recognition module was validated using Google Colab and was developed using the Long Short Term Memory (LSTM) neural network, achieving an accuracy of 97.04%. After the processes were created, it was necessary to integrate the technologies. Unfortunately, due to hardware limitations, it was not possible to implement facial recognition verification. However, the necessary machine learning algorithms and models for facial recognition were developed and tested on a computer using the MOBIO database. The final system includes password and RFID tag entry options, and despite this limitation, the obtained results were satisfactory, allowing access control only for registered individuals. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-05-24T15:13:17Z 2023-05-24T15:13:17Z 2023-02-24 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/bachelorThesis |
format |
bachelorThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://riu.ufam.edu.br/handle/prefix/6638 |
url |
http://riu.ufam.edu.br/handle/prefix/6638 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Brasil FT - Faculdade de Tecnologia Manaus (AM) Engenharia Elétrica – Eletrônica - Bacharelado - Manaus |
publisher.none.fl_str_mv |
Brasil FT - Faculdade de Tecnologia Manaus (AM) Engenharia Elétrica – Eletrônica - Bacharelado - Manaus |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFAM instname:Universidade Federal do Amazonas (UFAM) instacron:UFAM |
instname_str |
Universidade Federal do Amazonas (UFAM) |
instacron_str |
UFAM |
institution |
UFAM |
reponame_str |
Repositório Institucional da UFAM |
collection |
Repositório Institucional da UFAM |
repository.name.fl_str_mv |
Repositório Institucional da UFAM - Universidade Federal do Amazonas (UFAM) |
repository.mail.fl_str_mv |
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1798061060857528320 |