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Polish Information Processing Society
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Annals of Computer Science and Information Systems, Volume 11

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

An Unsupervised Evidential Conflict Resolution Method for Data Fusion In IoT

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DOI: http://dx.doi.org/10.15439/2017F122

Citation: Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 11, pages 819–823 ()

Full text

Abstract. Internet of Things (IoT) has gained substantial attention recently and plays a significant role in multiple real-world application deployments. A wide spectrum of such applications strongly depend on data fusion capabilities in the cloud from diverse information sources. In fact, various information sources often provide conflicting and contradictory for the same object, and thus it is important to fuse and resolve any possible information conflict before taking crucial decisions. For this reason, the primary aim of this paper is to provide a new evidential conflict resolution method that is able to automatically solve the problem of contradictory information provided by different sources in IoT applications. This method is based on the belief functions theory which is a powerful mathematical theory that can represent and manipulate various types if information imperfection. The performance of the proposed method was evaluated through simulation experiments. The results from these simulations demonstrated that our method outperforms the state-of-art methods in terms of effectiveness.

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