A real-time data mining framework for adaptive lighting systems

2020 ◽  
Author(s):  
Dorukalp Durmus
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Real Time ◽  
Lighting System ◽  
Time Data ◽  
Data Mining Techniques ◽  
Real Time Data ◽  
Lighting Systems

An adaptive lighting system can operate in real-time by adjusting its output through a decision-making algorithm based on data mining techniques.

scholarly journals A real-time data mining framework for adaptive lighting systems

2020 ◽  
Author(s):  
Dorukalp Durmus
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Real Time ◽  
Lighting System ◽  
Time Data ◽  
Data Mining Techniques ◽  
Real Time Data ◽  
Lighting Systems

An adaptive lighting system can operate in real-time by adjusting its output through a decision-making algorithm based on data mining techniques.

Integrated E-Marketing-A Strategy-Driven Technical Analysis Framework

2011 ◽  
pp. 317-327
Author(s):  
Simpson Poon ◽  
Irfan Altas ◽  
Geoff Fellows
Keyword(s):  
Data Mining ◽  
Real Time ◽  
Empirical Data ◽  
Integrated Approach ◽  
Strategy Formulation ◽  
Time Data ◽  
Data Mining Techniques ◽  
Marketing Campaign ◽  
Potential Problems ◽  
Real Time Data

E-marketing is considered to be one of the key applications in e-business but so far there has been no sure-fire formula for success. One of the problems is that although we can gather visitor information through behaviours online (e.g., cookies and Weblogs), often there is not an integrated approach to link up strategy formulation with empirical data. In this chapter, we propose a framework that addresses the issue of real-time objective-driven e-marketing. We present approaches that combine real-time data packet analysis integrated with data mining techniques to create a responsive e-marketing campaign. Finally, we discuss some of the potential problems facing e-marketers in the future.

scholarly journals The Importance of Implementing Cyber Physical Systems to Acquire Real-Time Data and Indicators

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 147-153
Author(s):  
Paula Morella ◽  
María Pilar Lambán ◽  
Jesús Antonio Royo ◽  
Juan Carlos Sánchez
Keyword(s):  
Decision Making ◽  
Data Acquisition ◽  
Real Time ◽  
Failure Detection ◽  
Cyber Physical Systems ◽  
Future Research ◽  
Time Data ◽  
Physical Systems ◽  
The Real ◽  
Real Time Data

Among the new trends in technology that have emerged through the Industry 4.0, Cyber Physical Systems (CPS) and Internet of Things (IoT) are crucial for the real-time data acquisition. This data acquisition, together with its transformation in valuable information, are indispensable for the development of real-time indicators. Moreover, real-time indicators provide companies with a competitive advantage over the competition since they enhance the calculus and speed up the decision-making and failure detection. Our research highlights the advantages of real-time data acquisition for supply chains, developing indicators that would be impossible to achieve with traditional systems, improving the accuracy of the existing ones and enhancing the real-time decision-making. Moreover, it brings out the importance of integrating technologies 4.0 in industry, in this case, CPS and IoT, and establishes the main points for a future research agenda of this topic.

Early Warning of Power Plant Equipment Based on Massive Real-Time Data Mining Technology

2014 ◽  
Vol 599-601 ◽  
pp. 1487-1490 ◽  
Author(s):  
Li Kun Zheng ◽  
Kun Feng ◽  
Xiao Qing Xiao ◽  
Wei Qiao Song
Keyword(s):  
Data Mining ◽  
Power Plant ◽  
Real Time ◽  
Early Warning ◽  
Time Data ◽  
Mining Technology ◽  
Equipment Safety ◽  
State Evaluation ◽  
Power Plant Equipment ◽  
Real Time Data

This paper mainly discusses the application of the mass real-time data mining technology in equipment safety state evaluation in the power plant and the realization of the equipment comprehensive quantitative assessment and early warning of potential failure by mining analysis and modeling massive amounts of real-time data the power equipment. In addition to the foundational technology introduced in this paper, the technology is also verified by the application case in the power supply side remote diagnosis center of Guangdong electric institute.

A Systematic Review About Prediction of Academic Behavior Through Data Mining Techniques

2020 ◽  
Vol 17 (11) ◽  
pp. 5162-5166
Author(s):  
Puninder Kaur ◽  
Amandeep Kaur ◽  
Rajwinder Kaur
Keyword(s):  
Systematic Review ◽  
Data Mining ◽  
Data Analysis ◽  
Educational Data Mining ◽  
Prediction Methods ◽  
Time Data ◽  
Academic Behavior ◽  
Data Mining Techniques ◽  
Real Time Data ◽  
Extract Information

In the IT world, predicting the academic performance of the huge student population poses a big challenge. Educational data mining techniques significantly contribute in providing solution to this problem. There are several prediction methods available for data classification and clustering, to extract information and provide accurate results. In this paper, different prediction methodologies are highlighted for the prediction of real-time data analysis of dynamic academic behavior of the students. The main focus is to provide brief knowledge about all data mining techniques and highlight dissimilarities among various methods in order to provide the best results for the students.

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