Juan Pablo Serrano-Rubio

Dr. Juan Pablo Serrano-Rubio


Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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24 February 2016 in Neural Processing Letters
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Journal Article
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JSJuan Pablo Serrano-Rubio
Juan Pablo Serrano-Rubio
AAArturo Hernández Aguirre
Arturo Hernández Aguirre
HHHerrera-Guzman Herrera-Guzman
Herrera-Guzman Herrera-Guzman

1 April 2020 in Expert Systems with Applications
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Journal Article
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ISIgnacio Segovia-Domínguez
Ignacio Segovia-Domínguez
RHRafael Herrera-Guzmán
Rafael Herrera-Guzmán
JSJuan Pablo Serrano-Rubio
Juan Pablo Serrano-Rubio
AHArturo Hernández-Aguirre
Arturo Hernández-Aguirre

1 August 2020 in Signal, Image and Video Processing
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Journal Article
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JSJuan Pablo Serrano-Rubio
Juan Pablo Serrano-Rubio
MRMateo D. M. Ruiz
Mateo D. M. Ruiz
UVUlises Vidal-Espitia
Ulises Vidal-Espitia

20 January 2017 in Soft Computing
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Journal Article
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JSJuan Pablo Serrano-Rubio
Juan Pablo Serrano-Rubio
AAArturo Hernández Aguirre
Arturo Hernández Aguirre
HHHerrera-Guzman Herrera-Guzman
Herrera-Guzman Herrera-Guzman

1 November 2019
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Conference Paper
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JAJose Alonso Aguirre-Nunez
Jose Alonso Aguirre-Nunez
LGLuis Manuel Garcia-Barajas
Luis Manuel Garcia-Barajas
JHJose de Jesus Hetnandez-Gomez
Jose de Jesus Hetnandez-Gomez
JSJuan Pablo Serrano-Rubio
Juan Pablo Serrano-Rubio
RHRafael Herrera-Guzman
Rafael Herrera-Guzman
The paradigm of the Internet of Things (IoT) has incorporated new applications for human daily life. Some of these applications are based on architectures which include wireless sensor-actuator networks. The information which is collected by the sensors is processed in order to decide when to enable or disable an actuator to perform a particular task. Often, the processing of the information is performed in the cloud consuming a lot of computing resources and bandwidth. In this paper, we propose a circuit which includes the SCT-013030 sensor and the ESP8266 NodeMcu V2 module for energy monitoring consumption in smart homes using a wireless sensor network. An artificial neural network is implemented using the processor of the ESP8266 NodeMcu module to recognise when there is unusual energy consumption in home appliances. The consumption information obtained by the wireless sensor is collected in a MySQL database, for which a Raspberry Pi 3B is used as server. Our artificial-neural-network-enabled circuit will be capable of warning the user of an abnormal energy consumption.

12 November 2014 in Lecture Notes in Computer Science
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Book Chapter
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JSJuan Pablo Serrano-Rubio
Juan Pablo Serrano-Rubio
AAArturo Hernández Aguirre
Arturo Hernández Aguirre
RGRafael Herrera Guzmán
Rafael Herrera Guzmán