scholarly journals Introduction to social sensing and big data computing for disaster management

2019 ◽  
Vol 12 (11) ◽  
pp. 1198-1204 ◽  
Author(s):  
Zhenlong Li ◽  
Qunying Huang ◽  
Christopher T. Emrich
IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 54595-54614 ◽  
Author(s):  
Syed Attique Shah ◽  
Dursun Zafer Seker ◽  
Sufian Hameed ◽  
Dirk Draheim

2016 ◽  
Vol 11 (2) ◽  
pp. 252-264
Author(s):  
Weidong Qiu ◽  
Bozhong Liu ◽  
Can Ge ◽  
Lingzhi Xu ◽  
Xiaoming Tang ◽  
...  

CHANCE ◽  
2013 ◽  
Vol 26 (2) ◽  
pp. 28-32 ◽  
Author(s):  
Nicole Lazar

Author(s):  
Mohamed Elsotouhy ◽  
Geetika Jain ◽  
Archana Shrivastava

The concept of big data (BD) has been coupled with disaster management to improve the crisis response during pandemic and epidemic. BD has transformed every aspect and approach of handling the unorganized set of data files and converting the same into a piece of more structured information. The constant inflow of unstructured data shows the research lacuna, especially during a pandemic. This study is an effort to develop a pandemic disaster management approach based on BD. BD text analytics potential is immense in effective pandemic disaster management via visualization, explanation, and data analysis. To seize the understanding of using BD toward disaster management, we have taken a comprehensive approach in place of fragmented view by using BD text analytics approach to comprehend the various relationships about disaster management theory. The study’s findings indicate that it is essential to understand all the pandemic disaster management performed in the past and improve the future crisis response using BD. Though worldwide, all the communities face big chaos and have little help reaching a potential solution.


2017 ◽  
Vol 77 (8) ◽  
pp. 10077-10089 ◽  
Author(s):  
Zhihan Lv ◽  
Xiaoming Li ◽  
Kim-Kwang Raymond Choo

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