Application of Marine Big Data in the Shanghai Storm Surge Disaster Assistant Decision-Making System

2019 ◽  
pp. 181-245
2018 ◽  
Vol 7 (3.1) ◽  
pp. 63 ◽  
Author(s):  
R Revathy ◽  
R Aroul Canessane

Data are vital to help decision making. On the off chance that data have low veracity, choices are not liable to be sound. Internet of Things (IoT) quality rates big data with error, irregularity, deficiency, trickery, and model guess. Improving data veracity is critical to address these difficulties. In this article, we condense the key qualities and difficulties of IoT, which impact data handling and decision making. We audit the scene of estimating and upgrading data veracity and mining indeterminate data streams. Also, we propose five suggestions for future advancement of veracious big IoT data investigation that are identified with the heterogeneous and appropriated nature of IoT data, self-governing basic leadership, setting mindful and area streamlined philosophies, data cleaning and handling procedures for IoT edge gadgets, and protection safeguarding, customized, and secure data administration.  


2020 ◽  
Author(s):  
Jincheng Wang ◽  
Jianhui Kan ◽  
Xufeng Wang ◽  
Wenxin He ◽  
Siyu Li ◽  
...  

2020 ◽  
Author(s):  
praveen kumar

Decision support system (DSS) in today’s world in era of Big Data Analytics (BDA) has shifted many fold from manual interpretation (Management centric) to more distributed hierarchy. More logical and accurate with BDA Ecosystem from judiciary to insurance. This paper will talk about sectors that has successfully adapted it. DSS with Predictive, prescriptive and descriptive analytics with data like visual, audio, syntactical, raw that too in auto mode as to give more accurate and interruption free solution to critical process. Hence aim is understand BDA to DSS implementation with modern and open source technologies like Hadoop, AWS, Apache suite etc.


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