Construction of Smart Campus in Universities Under the Background of Big Data Intelligence

Author(s):  
Wengao Sun
Keyword(s):  
Big Data ◽  
2019 ◽  
Vol 3 (2) ◽  
pp. 152
Author(s):  
Xianglan Wu

<p>In today's society, the rise of the Internet and rapid development make every day produce a huge amount of data. Therefore, the traditional data processing mode and data storage can not be fully analyzed and mined these data. More and more new information technologies (such as cloud computing, virtualization and big data, etc.) have emerged and been applied, the network has turned from informationization to intelligence, and campus construction has ushered in the stage of smart campus construction.The construction of intelligent campus refers to big data and cloud computing technology, which improves the informatization service quality of colleges and universities by integrating, storing and mining huge data.</p>


2019 ◽  
Vol 11 (20) ◽  
pp. 5552 ◽  
Author(s):  
William Villegas-Ch ◽  
Jhoann Molina-Enriquez ◽  
Carlos Chicaiza-Tamayo ◽  
Iván Ortiz-Garcés ◽  
Sergio Luján-Mora

At present, university campuses integrate technologies such as the internet of things, cloud computing, and big data, among others, which provide support to the campus to improve their resource management processes and learning models. Integrating these technologies into a centralized environment allows for the creation of a controlled environment and, subsequently, an intelligent environment. These environments are ideal for generating new management methods that can solve problems of global interest, such as resource consumption. The integration of new technologies also allows for the focusing of its efforts on improving the quality of life of its inhabitants. However, the comfort and benefits of technology must be developed in a sustainable environment where there is harmony between people and nature. For this, it is necessary to improve the energy consumption of the smart campus, which is possible by constantly monitoring and analyzing the data to detect any anomaly in the system. This work integrates a big data framework capable of analyzing the data, regardless of its format, providing effective and efficient responses to each process. The method developed is generic, which allows for its application to be adequate in addressing the needs of any smart campus.


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