scholarly journals Real-Time Data Visualisation in Collaborative Virtual Environment for Emergency Management

Author(s):  
Pan Wang ◽  
Ian Bishop

A collaborative virtual environment (CVE) is a shared virtual environment used for collaboration of many participants that may be spread over large distances. CVEs have been widely used in emergency management, especially for education, training and assessment. This paper describes the design and implementation of a prototype system that facilitates emergency management via a CVE using real-time spatial information. In particular, a method for automatic integration, modeling and visual simulation using real-time data from multiple online sources is proposed. Moreover, strategies are presented for using CVE-based scenarios for carrying out training, and testing preparedness measures. A novel technique has also been developed for real-time situation monitoring. Based on a system development (SD) research approach, the performance and functionality of the system was tested and evaluated. The use of real-time data acquisition and simulation was deemed to improve the processes of emergency management by increasing engagement, enhancing training and supporting decision-making of first responders and emergency managers.

2013 ◽  
Vol 373-375 ◽  
pp. 888-891
Author(s):  
Fang Liu ◽  
Wei Tong ◽  
Zhi Jun Qian ◽  
Yu Hong Dong

This paper introduced the laboratory model of Real-time monitor system based on the 3D Visualization for calefaction furnace, depicted the process of the model.In this paper we created a virtual environment and transport the real-time data which we collected from the locale to the virtual scene,to realize the real time monitor on the real environment.Through simulating in the lab,the effect of this system was realistic at the same time it arrived at the goal of better monitoring with better real-time.


2011 ◽  
Vol 189-193 ◽  
pp. 2621-2624
Author(s):  
Hai Wang

Mining from the equipment/technology process historical data can find diagnosis knowledge. Real-time analysis and evaluation on the status of equipment can be realized based on its current state parameters and historical information, which detect the potential fault rapidly and protect equipment to avoid failures further. This paper did an in-depth study in real-time data-based fault diagnosis system, built a real-time data integration platform and accomplished intelligent diagnosis method by ANFIS networks with the mined historical data. The production process was diagnosed and evaluated online with this diagnosis method. Combined with actual production system, its prototype system was developed.


Author(s):  
M. Li ◽  
H. Liu ◽  
C. Yang

The development of high-sulfur gas fields, also known as sour gas field, is faced with a series of safety control and emergency management problems. The GIS-based emergency response system is placed high expectations under the consideration of high pressure, high content, complex terrain and highly density population in Sichuan Basin, southwest China. The most researches on high hydrogen sulphide gas dispersion simulation and evaluation are used for environmental impact assessment (EIA) or emergency preparedness planning. This paper introduces a real-time GIS platform for high-sulfur gas emergency response. Combining with real-time data from the leak detection systems and the meteorological monitoring stations, GIS platform provides the functions of simulating, evaluating and displaying of the different spatial-temporal toxic gas distribution patterns and evaluation results. This paper firstly proposes the architecture of Emergency Response/Management System, secondly explains EPA’s Gaussian dispersion model CALPUFF simulation workflow under high complex terrain and real-time data, thirdly explains the emergency workflow and spatial analysis functions of computing the accident influencing areas, population and the optimal evacuation routes. Finally, a well blow scenarios is used for verify the system. The study shows that GIS platform which integrates the real-time data and CALPUFF models will be one of the essential operational platforms for high-sulfur gas fields emergency management.


Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 399-P
Author(s):  
ANN MARIE HASSE ◽  
RIFKA SCHULMAN ◽  
TORI CALDER

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