Comparison of deep learning models for predictive maintenance

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Abstract

There is a clear intersection between the Internet of Things (IoT) and Artificial Intelligence (AI). IoT is about connecting machines and making use of the data generated from those machines. AI is about simulating intelligent behaviour in machines of all kinds. As IoT devices will generate vast amounts of data, then AI will be functionally necessary to deal with these huge volumes if we're to have any chance of making sense of the data. AI is beneficial for both real-time and post event processing: Post event processing-identifying patterns in data sets and running predictive analytics, e.g. the correlation between traffic congestion, air pollution and chronic respiratory illnesses within a city centre. Real-time processing-responding quickly to conditions and building up knowledge of decisions about those events, e.g. remote video camera reading license plates for parking payments.

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Naren, R., & Subhashini, J. (2020). Comparison of deep learning models for predictive maintenance. In IOP Conference Series: Materials Science and Engineering (Vol. 912). IOP Publishing Ltd. https://doi.org/10.1088/1757-899X/912/2/022029

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