Application of a Big Data Framework for Data Monitoring on a Smart Campus

William Villegas-Ch, Jhoann Molina-Enriquez, Carlos Chicaiza-Tamayo, Iván Ortiz-Garcés and Sergio Luján-Mora
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William Villegas-Ch: Escuela de Ingeniería en Tecnologías de la Información, FICA, Universidad de Las Américas, 170125 Quito, Ecuador
Jhoann Molina-Enriquez: Escuela de Ingeniería en Tecnologías de la Información, FICA, Universidad de Las Américas, 170125 Quito, Ecuador
Carlos Chicaiza-Tamayo: Escuela de Ingeniería en Tecnologías de la Información, FICA, Universidad de Las Américas, 170125 Quito, Ecuador
Iván Ortiz-Garcés: Escuela de Ingeniería en Tecnologías de la Información, FICA, Universidad de Las Américas, 170125 Quito, Ecuador
Sergio Luján-Mora: Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, 03690 Alicante, Spain

Sustainability, 2019, vol. 11, issue 20, 1-15

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.

Keywords: smart campus; big data; Hadoop (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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