A comparative study of classification techniques for managing iot devices of common specifications

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Abstract

As information technology and telecommunication systems continue to grow in size and complexity, especially with the Internet of Things (IoT) domain that is being hailed as the next industrial revolution, emerging technologies have to anticipate this dramatic increase of heterogeneous connected devices. This paper proposes a solution that can be used to manage this huge number of devices, by classifying them and predicting their device’s type, based on their specifications. Four (4) classification algorithms are being applied on a dataset containing the specifications of known devices (in terms of known device type), which is being used for predicting the unknown devices’ types. These algorithms are analyzed using the WEKA data mining tool and a comparative study is undertaken to find the classifier that performs the best analysis on the dataset obtained, using a set of predefined performance metrics to compare the results of each classifier.

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Mavrogiorgou, A., Kiourtis, A., & Kyriazis, D. (2017). A comparative study of classification techniques for managing iot devices of common specifications. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10537 LNCS, pp. 67–77). Springer Verlag. https://doi.org/10.1007/978-3-319-68066-8_6

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