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Real-time Probabilistic Data Fusion for Large-scale IoT Applications

Akbar, Adnan, Kousiouris, George, Pervaiz, Haris bin, Sancho, Juan, Ta-Shma, Paula, Carrez, Francois and Moessner, Klaus (2018) Real-time Probabilistic Data Fusion for Large-scale IoT Applications IEEE Access, 6. pp. 10015-10027.

Real-time Probabilistic Data Fusion for Large-scale IoT Applications.pdf - Accepted version Manuscript

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IoT data analytics is underpinning numerous applications, however the task is still challenging predominantly due to heterogeneous IoT data streams, unreliable networks and ever increasing size of the data. In this context, we propose a two layer architecture for analyzing IoT data. The first layer provides a generic interface using a service oriented gateway to ingest data from multiple interfaces and IoT systems, store it in a scalable manner and analyze it in real-time to extract high-level events whereas second layer is responsible for probabilistic fusion of these high-level events. In the second layer, we extend state-ofthe- art event processing using Bayesian networks (BNs) in order to take uncertainty into account while detecting complex events. We implement our proposed solution using open source components optimized for large-scale applications. We demonstrate our solution on real-world use-case in the domain of intelligent transportation system (ITS) where we analysed traffic, weather and social media data streams from Madrid city in order to predict probability of congestion in real-time. The performance of the system is evaluated qualitatively using a web-interface where traffic administrators can provide the feedback about the quality of predictions and quantitatively using F-measure with an accuracy of over 80%.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Kousiouris, George
Pervaiz, Haris
Sancho, Juan
Ta-Shma, Paula
Date : 9 February 2018
DOI : 10.1109/ACCESS.2018.2804623
Copyright Disclaimer : © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works
Uncontrolled Keywords : Complex event processing; Data analysis; Internet of things; Real-time systems; Intelligent transportation systems
Depositing User : Clive Harris
Date Deposited : 08 Feb 2018 11:32
Last Modified : 16 Jan 2019 19:07

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