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Conference Paper/Proceeding/Abstract 815 views

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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first_indexed 2018-04-11T19:34:04Z
last_indexed 2018-04-23T19:31:33Z
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spelling 2018-04-23T14:26:56.3804702 v2 39371 2018-04-11 BRECCIA: A novel multi-source fusion framework for dynamic geospatial data analysis a88a07c43b3e80f27cb96897d1bc2534 Xiuyi Fan Xiuyi Fan true false 2018-04-11 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. Conference Paper/Proceeding/Abstract 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI) 390 396 IEEE Daegu, South Korea 978-1-5090-6065-8 9781509060641 11 12 2017 2017-12-11 10.1109/mfi.2017.8170352 COLLEGE NANME COLLEGE CODE Swansea University 2018-04-23T14:26:56.3804702 2018-04-11T18:37:59.9831577 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science D. Sacharny 1 T. C. Henderson 2 R. Simmons 3 A. Mitiche 4 T. Welker 5 Xiuyi Fan 6
title BRECCIA: A novel multi-source fusion framework for dynamic geospatial data analysis
spellingShingle BRECCIA: A novel multi-source fusion framework for dynamic geospatial data analysis
Xiuyi Fan
title_short BRECCIA: A novel multi-source fusion framework for dynamic geospatial data analysis
title_full BRECCIA: A novel multi-source fusion framework for dynamic geospatial data analysis
title_fullStr BRECCIA: A novel multi-source fusion framework for dynamic geospatial data analysis
title_full_unstemmed BRECCIA: A novel multi-source fusion framework for dynamic geospatial data analysis
title_sort BRECCIA: A novel multi-source fusion framework for dynamic geospatial data analysis
author_id_str_mv a88a07c43b3e80f27cb96897d1bc2534
author_id_fullname_str_mv a88a07c43b3e80f27cb96897d1bc2534_***_Xiuyi Fan
author Xiuyi Fan
author2 D. Sacharny
T. C. Henderson
R. Simmons
A. Mitiche
T. Welker
Xiuyi Fan
format Conference Paper/Proceeding/Abstract
container_title 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)
container_start_page 390
publishDate 2017
institution Swansea University
isbn 978-1-5090-6065-8
9781509060641
doi_str_mv 10.1109/mfi.2017.8170352
publisher IEEE
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 0
active_str 0
description 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.
published_date 2017-12-11T03:49:59Z
_version_ 1763752437221425152
score 11.013731

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