A Generic Survey on Medical Big Data Analysis Using Internet of Things

2018 ◽  
pp. 265-276 ◽  
Author(s):  
Sumanta Kuila ◽  
Namrata Dhanda ◽  
Subhankar Joardar ◽  
Sarmistha Neogy ◽  
Jayanta Kuila
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Internet Of Things ◽  
Big Data Analysis ◽  
Medical Big Data

scholarly journals A monitoring method of semiconductor manufacturing processes using Internet of Things–based big data analysis

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771772181 ◽  
Author(s):  
Seok-Woo Jang ◽  
Gye-Young Kim
Keyword(s):  
Time Series ◽  
Big Data ◽  
Data Analysis ◽  
Internet Of Things ◽  
Real Time ◽  
Semiconductor Manufacturing ◽  
Reference Model ◽  
Big Data Analysis ◽  
Monitoring Method ◽  
Manufacturing Equipment

This article proposes an intelligent monitoring system for semiconductor manufacturing equipment, which determines spec-in or spec-out for a wafer in process, using Internet of Things–based big data analysis. The proposed system consists of three phases: initialization, learning, and prediction in real time. The initialization sets the weights and the effective steps for all parameters of equipment to be monitored. The learning performs a clustering to assign similar patterns to the same class. The patterns consist of a multiple time-series produced by semiconductor manufacturing equipment and an after clean inspection measured by the corresponding tester. We modify the Line, Buzo, and Gray algorithm for classifying the time-series patterns. The modified Line, Buzo, and Gray algorithm outputs a reference model for every cluster. The prediction compares a time-series entered in real time with the reference model using statistical dynamic time warping to find the best matched pattern and then calculates a predicted after clean inspection by combining the measured after clean inspection, the dissimilarity, and the weights. Finally, it determines spec-in or spec-out for the wafer. We will present experimental results that show how the proposed system is applied on the data acquired from semiconductor etching equipment.

Price Versus Performance of Big Data Analysis for Cloud Based Internet of Things Networks

2018 ◽  
Vol 24 (3) ◽  
pp. 1078-1094 ◽  
Author(s):  
Khalim Amjad Meerja ◽  
Praveen V. Naidu ◽  
Sri Rama Krishna Kalva
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Internet Of Things ◽  
Big Data Analysis

The Role of Visual Assessment of Clusters for Big Data Analysis: From Real-World Internet of Things

2020 ◽  
Vol 6 (4) ◽  
pp. 45-53
Author(s):  
Marimuthu Palaniswami ◽  
Aravinda S. Rao ◽  
Dheeraj Kumar ◽  
Punit Rathore ◽  
Sutharshan Rajasegarar
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Internet Of Things ◽  
Real World ◽  
Visual Assessment ◽  
Big Data Analysis

scholarly journals IoT-Fog-Cloud system architecture for big data analysis and cybersecurity systems: a review of fog computing, the introduction to the Internet of Things audit

2020 ◽  
Author(s):  
D. R. Kolisnyk ◽  
◽  
K. S. Misevych ◽  
S. V. Kovalenko
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Internet Of Things ◽  
System Architecture ◽  
Fog Computing ◽  
Big Data Analysis ◽  
Future Research ◽  
The Internet ◽  
Security Issues ◽  
The Internet Of Things

The article considers the issues of system architecture IoT-Fog-Cloud, considers the interaction between the three levels of IoT, Fog and Cloud for the effective implementation of programs for big data analysis and cybersecurity. The article also discusses security issues, solutions and directions for future research in the field of the Internet of Things and nebulous computing.

scholarly journals Information Security Terminal Architecture of Power Transportation Mobile Internet of Things Based on Big Data Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xianzhi Tang ◽  
Chunyan Ding
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Information Security ◽  
Internet Of Things ◽  
Power System ◽  
Big Data Analysis ◽  
The Internet ◽  
Mobile Information ◽  
Internet Of Things Technology ◽  
The Internet Of Things

The progress of the social economy and the rapid development of the power field have created more favorable conditions for the construction of my country’s power grid. In this network age, how to further realize the connection between the power system and the Internet of Things is the key content of many scholars’ research. In the Internet of Things environment, there have been many excellent results in the collection, storage, and management of electric power big data, but the problem of information security has not been completely solved. Based on big data analysis and Internet of Things technology, this paper studies the architecture design of power information security terminals. In view of the diverse types of power grid mobile information and the large amount of data, this paper designs a power transportation mobile information security management system structure, which improves the effective management of power data by the system through big data, smart sensors, and wireless communication technology. According to the experiment, the power information security terminal constructed in this paper can effectively reduce communication resources and save communication costs in the process of aggregating multidimensional data. In the user satisfaction survey, residents’ satisfaction with the convenience and safety of the intelligent power system is also as high as 9.312 and 9.233. On the whole, the application of big data and Internet of Things technology to the construction of power information security terminals can indeed improve the service efficiency of power companies under the premise of ensuring safety and allow users to have a better experience.

scholarly journals How to Determine the Early Warning Threshold Value of Meteorological Factors on Influenza through Big Data Analysis and Machine Learning

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Hui Ge ◽  
Debao Fan ◽  
Ming Wan ◽  
Lizhu Jin ◽  
Xiaofeng Wang ◽  
...  
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Infectious Diseases ◽  
Early Warning ◽  
Meteorological Factors ◽  
Threshold Value ◽  
Big Data Analysis ◽  
Meteorological Conditions ◽  
Medical Big Data ◽  
Influenza Outbreaks

Infectious diseases are a major health challenge for the worldwide population. Since their rapid spread can cause great distress to the real world, in addition to taking appropriate measures to curb the spread of infectious diseases in the event of an outbreak, proper prediction and early warning before the outbreak of the threat of infectious diseases can provide an important basis for early and reasonable response by the government health sector, reduce morbidity and mortality, and greatly reduce national losses. However, if only traditional medical data is involved, it may be too late or too difficult to implement prediction and early warning of an infectious outbreak. Recently, medical big data has become a research hotspot and has played an increasingly important role in public health, precision medicine, and disease prediction. In this paper, we focus on exploring a prediction and early warning method for influenza with the help of medical big data. It is well known that meteorological conditions have an influence on influenza outbreaks. So, we try to find a way to determine the early warning threshold value of influenza outbreaks through big data analysis concerning meteorological factors. Results show that, based on analysis of meteorological conditions combined with influenza outbreak history data, the early warning threshold of influenza outbreaks could be established with reasonable high accuracy.

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