Data Prediction in Datasets of Internet of Things with Recurrent Neural Networks

Janine Kniess; Samuel Silva de Oliveira

doi:10.20944/preprints202311.0247.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 2 November 2023 / Approved: 3 November 2023 / Online: 3 November 2023 (12:38:10 CET)

The emergence of the Internet of Things (IoT) has led to the deployment of various types of sensors in many application fields, including environment monitoring, smart cities, health, industries, and others. The increasing number of connected devices has led to the creation of massive quantities of data that need to be analyzed. Typically, this data is ordered by time, as a time series. In this context, this paper presents a time series prediction model based on Recurrent Neural Networks in order to predict one step ahead. Result obtained through five Internet of Things monitoring datasets, showed that the Recurrent Neural Network obtained better performance that the prediction methods, ARIMA and SVM.

Dataset; Recurrent Neural Networks; Internet of Things; Time Series.

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

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Data Prediction in Datasets of Internet of Things with Recurrent Neural Networks

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