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Sensors (Basel). 2018 Dec 25;19(1). pii: E70. doi: 10.3390/s19010070.

Managing Devices of a One-to-One Computing Educational Program Using an IoT Infrastructure.

Author information

1
Instituto de Computación (INCO), Universidad de la República (UdelaR), Montevideo 11300, Uruguay. felipe.osimani@fing.edu.uy.
2
Instituto de Computación (INCO), Universidad de la República (UdelaR), Montevideo 11300, Uruguay. bruno.stecanella@fing.edu.uy.
3
Centro Ceibal para el Apoyo a la Educación de la Niñez y la Adolescencia (Plan Ceibal), Montevideo 11500, Uruguay. gcapdehourat@ceibal.edu.uy.
4
Instituto de Computación (INCO), Universidad de la República (UdelaR), Montevideo 11300, Uruguay. lorenae@fing.edu.uy.
5
Instituto de Computación (INCO), Universidad de la República (UdelaR), Montevideo 11300, Uruguay. grampin@fing.edu.uy.

Abstract

Plan Ceibal is the name coined in Uruguay for the local implementation of the One Laptop Per Child (OLPC) initiative. Plan Ceibal distributes laptops and tablets to students and teachers, and also deploys a nationwide wireless network to provide Internet access to these devices, provides video conference facilities, and develops educational applications. Given the scale of the program, management in general, and specifically device management, is a very challenging task. Device maintenance and replacement is a particularly important process; users trigger such kind of replacement processes and usually imply several days without the device. Early detection of fault conditions in the most stressed hardware parts (e.g., batteries) would permit to prompt defensive replacement, contributing to reduce downtime, and improving the user experience. Seeking for better, preventive and scalable device management, in this paper we present a prototype of a Mobile Device Management (MDM) module for Plan Ceibal, developed over an IoT infrastructure, showing the results of a controlled experiment over a sample of the devices. The prototype is deployed over a public IoT infrastructure to speed up the development process, avoiding, in this phase, the need for local infrastructure and maintenance, while enforcing scalability and security requirements. The presented data analysis was implemented off-line and represents a sample of possible metrics which could be used to implement preventive management in a real deployment.

KEYWORDS:

Internet of Things; Mobile Device Management; one-to-one computing educational program

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