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BRECCIA: A novel multi-source fusion framework for dynamic geospatial data analysis

D. Sacharny, T. C. Henderson, R. Simmons, A. Mitiche, T. Welker, Xiuyi Fan

2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), Pages: 390 - 396

Swansea University Author: Xiuyi Fan

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DOI (Published version): 10.1109/mfi.2017.8170352

Abstract

Geospatial Intelligence analysis involves the combination of multi-source information expressed in logical form, computational form, and sensor data. Each of these forms has its own way to describe uncertainty or error: e.g., frequency models, algorithmic truncation, floating point roundoff, Gaussia...

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Published in: 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)
ISBN: 978-1-5090-6065-8 9781509060641
Published: Daegu, South Korea IEEE 2017
URI: https://cronfa.swan.ac.uk/Record/cronfa39371
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Abstract: Geospatial Intelligence analysis involves the combination of multi-source information expressed in logical form, computational form, and sensor data. Each of these forms has its own way to describe uncertainty or error: e.g., frequency models, algorithmic truncation, floating point roundoff, Gaussian distributions, etc. We propose BRECCIA, a Geospatial Intelligence analysis system, which receives information from humans (as logical sentences), simulations (e.g., weather or environmental predictions), and sensors (e.g. cameras, weather stations, microphones, etc.), where each piece of information has an associated uncertainty; BRECCIA then provides responses to user queries based on a new probabilistic logic system which determines a coherent overall response to the query and the probability of that response; this new method avoids the exponential complexity of previous approaches. In addition, BRECCIA attempts to identify concrete mechanisms (proposed actions) to acquire new data dynamically in order to reduce the uncertainty of the query response. The basis for this is a novel approach to probabilistic argumentation analysis.
College: College of Science
Start Page: 390
End Page: 396