An Ontology-Underpinned Emergency Response System for Water Pollution Accidents

作者:Meng, Xiaoliang; Xu, Chao; Liu, Xinxia*; Bai, Junming; Zheng, Wenhan; Chang, Hao; Chen, Zhuo
来源:Sustainability, 2018, 10(2): 546.
DOI:10.3390/su10020546

摘要

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.