Estimating fire weather indices via semantic reasoning over wireless sensor network data streams

Gao, Lianli, Bruenig, Michael and Hunter, Jane (2014) Estimating fire weather indices via semantic reasoning over wireless sensor network data streams. International Journal of Web and Semantic Technology, 5 4: 1-20. doi:10.5121/ijwest.2014.5401


Author Gao, Lianli
Bruenig, Michael
Hunter, Jane
Title Estimating fire weather indices via semantic reasoning over wireless sensor network data streams
Journal name International Journal of Web and Semantic Technology   Check publisher's open access policy
ISSN 0976-2280
0975-9026
Publication date 2014-10
Sub-type Article (original research)
DOI 10.5121/ijwest.2014.5401
Open Access Status DOI
Volume 5
Issue 4
Start page 1
End page 20
Total pages 20
Place of publication Chennai, Tamil Nadu, India
Publisher A I R C C Publishing
Collection year 2015
Language eng
Formatted abstract
Wildfires are frequent, devastating events in Australia that regularly cause significant loss of life and widespread property damage. Fire weather indices are a widely-adopted method for measuring fire danger and they play a significant role in issuing bushfire warnings and in anticipating demand for bushfire management resources. Existing systems that calculate fire weather indices are limited due to low spatial and temporal resolution. Localized wireless sensor networks, on the other hand, gather continuous sensor data measuring variables such as air temperature, relative humidity, rainfall and wind speed at high resolutions. However, using wireless sensor networks to estimate fire weather indices is a challenge due to data quality issues, lack of standard data formats and lack of agreement on thresholds and methods for calculating fire weather indices. Within the scope of this paper, we propose a standardized approach to calculating Fire Weather Indices (a.k.a. fire danger ratings) and overcome a number of the challenges by applying Semantic Web Technologies to the processing of data streams from a wireless sensor network deployed in the Springbrook region of South East Queensland. This paper describes the underlying ontologies, the semantic reasoning and the Semantic Fire Weather Index (SFWI) system that we have developed to enable domain experts to specify and adapt rules for calculating Fire Weather Indices. We also describe the Web-based mapping interface that we have developed, that enables users to improve their understanding of how fire weather indices vary over time within a particular region. Finally, we discuss our evaluation results that indicate that the proposed system outperforms state-of-the-art techniques in terms of accuracy, precision and query performance.
Keyword Fire weather indices
Ontology
Semantic reasoning
Wireless sensor network
SPARQL
Sensor data streams
IDW
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
School of Information Technology and Electrical Engineering Publications
 
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Created: Fri, 20 Feb 2015, 13:56:29 EST by Professor Jane Hunter on behalf of School of Information Technol and Elec Engineering