scholarly journals Large-scale Real-time Data-driven Scientific Applications

2011 ◽  
Author(s):  
Junwei Cao ◽  
Junwei Li
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Data Driven ◽  
Scientific Applications ◽  
Time Data ◽  
Real Time Data

Fog-Enabled Architecture for Data-Driven Cyber-Manufacturing Systems

2016 ◽  
Author(s):  
Dazhong Wu ◽  
Janis Terpenny ◽  
Li Zhang ◽  
Robert Gao ◽  
Thomas Kurfess
Keyword(s):  
Real Time ◽  
Data Storage ◽  
Manufacturing Systems ◽  
Large Scale ◽  
Failure Detection ◽  
Remote Access ◽  
Data Driven ◽  
Time Data ◽  
Real Time Data ◽  
Geographically Distributed

Over the past few decades, both small- and medium-sized manufacturers as well as large original equipment manufacturers (OEMs) have been faced with an increasing need for low cost and scalable intelligent manufacturing machines. Capabilities are needed for collecting and processing large volumes of real-time data generated from manufacturing machines and processes as well as for diagnosing the root cause of identified defects, predicting their progression, and forecasting maintenance actions proactively to minimize unexpected machine down times. Although cloud computing enables ubiquitous and instant remote access to scalable information and communication technology (ICT) infrastructures and high volume data storage, it has limitations in latency-sensitive applications such as high performance computing and real-time stream analytics. The emergence of fog computing, Internet of Things (IoT), and cyber-physical systems (CPS) represent radical changes in the way sensing systems, along with ICT infrastructures, collect and analyze large volumes of real-time data streams in geographically distributed environments. Ultimately, such technological approaches enable machines to function as an agent that is capable of intelligent behaviors such as automatic fault and failure detection, self-diagnosis, and preventative maintenance scheduling. The objective of this research is to introduce a fog-enabled architecture that consists of smart sensor networks, communication protocols, parallel machine learning software, and private and public clouds. The fog-enabled architecture will have the potential to enable large-scale, geographically distributed online machine and process monitoring, diagnosis, and prognosis that require low latency and high bandwidth in the context of data-driven cyber-manufacturing systems.

Heart Watch: Dynamical Systems Based Real Time Data Driven ECG Synthesis

2021 ◽  
Author(s):  
Ashutosh Simha ◽  
Suryansh Sharma ◽  
Sujay Narayana ◽  
R. Venkatesh Prasad
Keyword(s):  
Dynamical Systems ◽  
Real Time ◽  
Data Driven ◽  
Time Data ◽  
Real Time Data

A REAL-TIME DATA-DRIVEN CONTROL SYSTEM FOR MULTI-MOTOR-DRIVEN MECHANISMS

2017 ◽  
Vol 32 (6) ◽  
Author(s):  
Huashan Liu ◽  
Lingbin Zeng ◽  
Wuneng Zhou ◽  
Shiqiang Zhu
Keyword(s):  
Control System ◽  
Real Time ◽  
Data Driven ◽  
Time Data ◽  
Real Time Data

scholarly journals Real-time data-driven interactive rough sketch inking

2018 ◽  
Vol 37 (4) ◽  
pp. 1-14 ◽  
Author(s):  
Edgar Simo-Serra ◽  
Satoshi Iizuka ◽  
Hiroshi Ishikawa
Keyword(s):  
Real Time ◽  
Data Driven ◽  
Time Data ◽  
Real Time Data
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