PRODUÇÃO ACADÊMICA Repositório Acadêmico da Graduação (RAG) TCC Engenharia de Computação
Use este identificador para citar ou linkar para este item: https://repositorio.pucgoias.edu.br/jspui/handle/123456789/1531
Tipo: Trabalho de Conclusão de Curso
Título: Automatic measurement of river water-level using image-based computer vision
Autor(es): Nascimento, Douglas Vieira do
Primeiro Orientador: Coelho, Clarimar José
metadata.dc.contributor.advisor-co1: Galvão Filho, Arlindo Rodrigues
metadata.dc.contributor.referee3: Carvalho, Rafael Viana de
Resumo: Monitoring the water reservoir in hydroelectric plants is of fundamental importance for the manage-ment of energy production, flood warnings and planning of water resources. To that end, telemetricand electronic meters allow water levels to be automatically measured and monitored in the hydroelec-tric power plant. Such methods may have flaws or inaccuracies, necessitating a second measurementmethod. Video surveillance has come to be widely used for monitoring as a redundant system, butit is still subject to human errors in visually reading information. In this context, this work proposesa redundant automatic measurement method using computer vision. As a case study, images fromconventional cameras from the Jirau Hydroelectric Power Plant, on the Madeira River, Brazil, wereused. The results obtained show RMSE, MAE and푅2errors of 0.045, 0.0328 and 0.9946 respectively.Such results show that the proposed model can collaborate as a redundant monitoring method.
Abstract: Monitoring the water reservoir in hydroelectric plants is of fundamental importance for the manage-ment of energy production, flood warnings and planning of water resources. To that end, telemetricand electronic meters allow water levels to be automatically measured and monitored in the hydroelec-tric power plant. Such methods may have flaws or inaccuracies, necessitating a second measurementmethod. Video surveillance has come to be widely used for monitoring as a redundant system, butit is still subject to human errors in visually reading information. In this context, this work proposesa redundant automatic measurement method using computer vision. As a case study, images fromconventional cameras from the Jirau Hydroelectric Power Plant, on the Madeira River, Brazil, wereused. The results obtained show RMSE, MAE and푅2errors of 0.045, 0.0328 and 0.9946 respectively.Such results show that the proposed model can collaborate as a redundant monitoring method
Palavras-chave: Water level measurement
Computer vision
Hidroeletric powerplant
CNPq: CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
Idioma: por
País: Brasil
Editor: Pontifícia Universidade Católica de Goiás
Sigla da Instituição: PUC Goiás
metadata.dc.publisher.department: Escola de Ciências Exatas e da Computação
Tipo de Acesso: Acesso Aberto
URI: https://repositorio.pucgoias.edu.br/jspui/handle/123456789/1531
Data do documento: 5-Jun-2021
Aparece nas coleções:TCC Engenharia de Computação

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