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Recurrent Neural Networks for Predicting Mobile Device State

Recurrent Neural Networks for Predicting Mobile Device State

Juan Manuel Rodriguez, Alejandro Zunino, Antonela Tommasel, Cristian Mateos
Copyright: © 2019 |Pages: 16
ISBN13: 9781522573685|ISBN10: 1522573682|EISBN13: 9781522573692
DOI: 10.4018/978-1-5225-7368-5.ch075
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MLA

Rodriguez, Juan Manuel, et al. "Recurrent Neural Networks for Predicting Mobile Device State." Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction, edited by Mehdi Khosrow-Pour, D.B.A., IGI Global, 2019, pp. 1028-1043. https://doi.org/10.4018/978-1-5225-7368-5.ch075

APA

Rodriguez, J. M., Zunino, A., Tommasel, A., & Mateos, C. (2019). Recurrent Neural Networks for Predicting Mobile Device State. In M. Khosrow-Pour, D.B.A. (Ed.), Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction (pp. 1028-1043). IGI Global. https://doi.org/10.4018/978-1-5225-7368-5.ch075

Chicago

Rodriguez, Juan Manuel, et al. "Recurrent Neural Networks for Predicting Mobile Device State." In Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction, edited by Mehdi Khosrow-Pour, D.B.A., 1028-1043. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-7368-5.ch075

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Abstract

Nowadays, mobile devices are ubiquitous in modern life as they allow users to perform virtually any task, from checking e-mails to playing video games. However, many of these operations are conditioned by the state of mobile devices. Therefore, knowing the current state of mobile devices and predicting their future states is a crucial issue in different domains, such as context-aware applications or ad-hoc networking. Several authors have proposed to use different machine learning methods for predicting some aspect of mobile devices' future states. This chapter aims at predicting mobile devices' battery charge, whether it is plugged to A/C, and screen and WiFi state. To fulfil this goal, the current state of a mobile device can be regarded as the consequence of the previous sequence of states, meaning that future states can be predicted by known previous ones. This chapter focuses on using recurrent neural networks for predicting future states.

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