An Ontology-Underpinned Emergency Response System for Water Pollution Accidents

Xiaoliang Meng, Chao Xu, Xinxia Liu, Junming Bai, Wenhan Zheng, Hao Chang and Zhuo Chen
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Xiaoliang Meng: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Chao Xu: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Xinxia Liu: School of Water Conservancy and Electric Power, Hebei University of Engineering, 62#Zhonghua Street, Handan 056038, China
Junming Bai: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Wenhan Zheng: Fujian Surveying and Mapping Institute, Fuzhou 350003, China
Hao Chang: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Zhuo Chen: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

Sustainability, 2018, vol. 10, issue 2, 1-18

Abstract: With the unceasing development and maturation of environment geographic information system, the response to water pollution accidents has been digitalized through the combination of monitoring sensors, management servers, and application software. However, most of these systems only achieve the basic and general geospatial data management and functional process tasks by adopting mechanistic water-quality models. To satisfy the sustainable monitoring and real-time emergency response application demand of the government and public users, it is a hotspot to study how to make the water pollution information being semantic and make the referred applications intelligent. Thus, the architecture of the ontology-underpinned emergency response system for water pollution accidents is proposed in this paper. This paper also makes a case study for usability testing of the water ontology models, and emergency response rules through an online water pollution emergency response system. The system contributes scientifically to the safety and sustainability of drinking water by providing emergency response and decision-making to the government and public in a timely manner.

Keywords: ontology; emergency response system; water pollution accident; reasoning; models (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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