Discussion on Power Grid Magnetic Storm Disaster Monitoring System Based on Cloud Computing

Liu, Di; Wang, Ying; Liu, Lian Guang

doi:10.4028/www.scientific.net/amr.341-342.641

Cited by 1 publication

(6 citation statements)

References 7 publications

(4 reference statements)

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“…Cloud Computing has had limited success in these areas due to the low levels of current integration between Cloud Computing and Geospatial Science. Li et al [33] used features of Cloud Computing to address the complex demands of data, storage, and processing for energy information management. The challenges of large-scale data management, analysis and processing of climate Science were handled using Cloud Computing by the introduction of community defined services such as Earth System Grid [34].…”

Section: Pros and Cons Of Cloud Computingmentioning

confidence: 99%

“…The historical information about the occurrences of the disasters was emphasized to make effective strategies to prevent the occurrence of flooding events by Wan et al [54] and health issues related disasters by Shen et al [85]. The extensive processing and analyses of multiple data were key to form effective strategies in the system proposed by Jiang et al [86], Liu et al [33] and Montoya [55]. The data processing framework proposed by Jiang et al [86] facilitated convenient and highly available processing of the forest pest control data to build an effective strategy for forest pest control.…”

Section: Preventionmentioning

confidence: 99%

“…The data processing framework proposed by Jiang et al [86] facilitated convenient and highly available processing of the forest pest control data to build an effective strategy for forest pest control. The monitoring system developed by Liu et al [33] focused on prevention of the disasters caused by magnetic storm facilitated by power system data, geomagnetic data, satellite data and other earth space observation data and their processing over the Clouds. Montoya [55] explored the use of low cost and rapid method of data collection for development of inventory based on combination of various technologies such as RS, GPS, Digital Video and GIS with multistage operations and analysis for prevention of disaster situations.…”

Section: Preventionmentioning

confidence: 99%

“…Li et al [35] used Cloud infrastructure to perform various complex Geospatial computing tasks such as FCD query, FCD map matching and speed computation for roadlinks for urban traffic monitoring. The power grid storm disaster monitoring system developed by Liu et al [33] used the features of Cloud Computing to solve the processing difficulties associated with largely massive geomagnetic data, satellite data and other earth space observation data.…”

Section: Cloud Infrastructurementioning

confidence: 99%

“…Shen et al [85] used Clouds for scalable, customizable and robust visualization of health services data obtained after various data processing and clustering steps. The monitoring system developed by Liu et al [33] and delivered through a wide range of devices allowed user access through a web browser, where desired services could be selected. The outputs of the ensemble run of a ground water model could be saved in Blob Storage after compression and downloaded by the user through a webbased interface in the system developed by Behzad et al [37].…”

Section: Visualizationmentioning

confidence: 99%

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Cloud Computing in natural hazard modeling systems: Current research trends and future directions

Garg

Hilton

et al. 2019

International Journal of Disaster Risk Reduction

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Every year, natural disasters cause major loss of human life, damage to infrastructure and significant economic impact on the areas involved. Geospatial Scientists aim to help in mitigating or managing such hazards by computational modeling of these complex events, while Information Communication Technology (ICT) supports the execution of various models addressing different aspects of disaster management. The execution of natural hazard models using traditional ICT foundations is not possible in a timely manner due to the complex nature of the models, the need for large-scale computational resources as well as intensive data and concurrent-access requirements. Cloud Computing can address these challenges with near-unlimited capacity for computation, storage and networking, and the ability to offer natural hazard modeling systems as end services has now become more realistic than ever. However, researchers face several challenges in adopting and utilizing Cloud Computing technologies in this area. Moreover, accessing the Cloud services during the disaster where the communication and power supply can break down, is still an open challenge. As such, this survey paper discusses these challenges, needs and existing problems to reflect the current research trends and outlines a conceptual Cloud-based solution framework for more effective natural hazards modeling and management systems using Cloud infrastructure in conjunction with other technologies such as Internet of Things(IoT) networks, fog and edge computing. We draw a clear picture of the current research state in the area and suggest further research directions for future systems.

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Section: Pros and Cons Of Cloud Computingmentioning

confidence: 99%