Browsing by Author "Orellana, Marcos"

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A middleware for managing the heterogeneity of data provining from IoT devices in ambient assisted living environments
(Institute of Electrical and Electronics Engineers Inc., 2020) Cedillo Orellana, Irene Priscila; Riofrío Machado, Xavier Fernando; Prado Cabrera, Katerine Daniela; Orellana, Marcos
Internet of Things (IoT) has been growing exponentially in the commercial market in recent years. It is also a fact that people hold one or more computing devices at home. Many of them have been developed to operate through internet connectivity with cloud computing technologies that result in the demand for fast, robust, and secure services. In most cases, the lack of these services makes difficult the transfer of data to fulfill the devices' purposes. Under these conditions, an intermediate layer or middleware is needed to process, filter, and send data through a more efficient alternative. This paper presents the adaptive solution of a middleware architecture as an intermediate layer between smart devices and cloud computing to enhance the management of the heterogeneity of data provining from IoT devices. The proposed middleware provides easy configuration, adaptability, and bearability for different environments. Finally, this solution has been implemented in the healthcare domain, in which IoT solutions are deployed into Ambient Assisted Living (AAL) environments.
A subject syllabus similarity analysis to address students mobility issue
(International Institute of Informatics and Systemics, IIIS, 2018) Saquicela Galarza, Víctor Hugo; Baculima Cumbe, John Fernando; Orellana, Gerardo; Orellana, Marcos; Piedra, Nelson; Espinoza Mejía, Jorge Mauricio; Vanegas Peralta, Pablo Fernando; Saquicela Galarza, Víctor Hugo
Currently, students' mobility in Higher Education has become very common and frequent. Although the transitioning process could be thought to be smooth and quick, students moving from one institution to another must go through rigorous and unfortunately, non-standardized academic validation processes. Usually, most part of the process, including credits recognition and syllabi comparison are manually performed, consuming excessive time and massive human effort. Some of these academic processes however, could be optimized by means of computer technologies, which support data processing and help solving real-life problems usually found in the academic field. In the specific case of Ecuador, we have identified that each Higher Education Institution (HEI) manages customized curricular information management systems which include non-standard syllabi structured documents. The existence of custom made formats at every HEI has originate a large variety of data models. In this work, we propose to address these problems by identifying similarities between different current syllabi of Ecuadorian HEIs, aiming to the optimization, integration and improvement of the academic activities related to the students' mobility processes, such as credits recognition. This proposal relies on the definition of a standard data model, which is used to describe the academic syllabus and that allows the implementation of a computer-based system focused on similarities detection through the use of semantic web technologies and text mining tools. Copyright © 2018 by the International Institute of Informatics and Systemics.
Application of the LSA technique to determine the priority of alerts from a command and control center
(Institute of Electrical and Electronics Engineers, 2021) Prado Cabrera, Katerine Daniela
It is essential to determine the alert level in a command-and-control center when someone calls an operator for an emergency since life may be in danger. The alert level is determined based on the evaluation that the operator can perceive during the call. Sometimes, cases can be similar to those previously attended. Therefore, it is helpful that this knowledge can be rescued and applied to new cases. In this context, the Latent Semantic Analysis (LSA) technique can determine the alert level and find the most representative words in each case. Thus, when a new alarm is triggered, the system can recommend the alert level with which it is rated. Consequently, a solution based on previous knowledge has been stated. This solution leads to the following methodological process: i) data preprocessing, ii) topic analysis and iii) classification. When this proposal was applied, the results revealed an accuracy greater than 60% in predicting the type of alert based on the text
Behavior analysis of atmospheric components and meteorological variables applying data mining association techniques
(Springer Science and Business Media Deutschland GmbH, 2021) Orellana, Marcos
The relationship between atmospheric components and meteorological variables is essential to assess the air quality and thus avoid citizens' health risks. However, finding an association relationship between those factors could be complicated due to the number of categorization methods that can be used (e.g., frequency, size, binning). Therefore, the objective of this study is to propose a methodology that prepares data through a discretization process and then applies association techniques of the possible combinations between the analyzed variables. The results show that the method used is effective in locating patterns, which are useful for the environmental manager to find knowledge