LiReD: A Light-Weight Real-Time Fault Detection System for Edge Computing Using LSTM Recurrent Neural Networks

Monitoring the status of the facilities and detecting any faults are considered an important technology in a smart factory. Although the faults of machine can be analyzed in real time using collected data, it requires a large amount of computing resources to handle the massive data. A cloud server c...

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Detalles Bibliográficos
Autores principales: Park, Donghyun, Kim, Seulgi, An, Yelin, Jung, Jae-Yoon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068676/
https://www.ncbi.nlm.nih.gov/pubmed/29966374
http://dx.doi.org/10.3390/s18072110

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068676/
https://www.ncbi.nlm.nih.gov/pubmed/29966374
http://dx.doi.org/10.3390/s18072110

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