Application of a Big Data Framework for Data Monitoring on a Smart Campus
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http://hdl.handle.net/10045/97288
Title: | Application of a Big Data Framework for Data Monitoring on a Smart Campus |
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Authors: | Villegas-CH, William | Molina-Enriquez, Jhoann | Chicaiza-Tamayo, Carlos | Ortiz-Garcés, Iván | Luján-Mora, Sergio |
Research Group/s: | Advanced deveLopment and empIrical research on Software (ALISoft) |
Center, Department or Service: | Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos |
Keywords: | Smart campus | Big data | Hadoop |
Knowledge Area: | Lenguajes y Sistemas Informáticos |
Issue Date: | 9-Oct-2019 |
Publisher: | MDPI |
Citation: | Villegas-Ch W, Molina-Enriquez J, Chicaiza-Tamayo C, Ortiz-Garcés I, Luján-Mora S. Application of a Big Data Framework for Data Monitoring on a Smart Campus. Sustainability. 2019; 11(20):5552. doi:10.3390/su11205552 |
Abstract: | 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. |
URI: | http://hdl.handle.net/10045/97288 |
ISSN: | 2071-1050 |
DOI: | 10.3390/su11205552 |
Language: | eng |
Type: | info:eu-repo/semantics/article |
Rights: | © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
Peer Review: | si |
Publisher version: | https://doi.org/10.3390/su11205552 |
Appears in Collections: | INV - ALISoft - Artículos de Revistas |
Files in This Item:
File | Description | Size | Format | |
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2019_Villegas-Ch_etal_Sustainability.pdf | 1,81 MB | Adobe PDF | Open Preview | |
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