TY - GEN
T1 - Artificial neuronal network for monitoring of energy consumption by a home device
AU - Ortega Castro, Juan Carlos
AU - Minchala, Luis I.
AU - Rodas, Ricardo Palacios
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - This paper presents the design of a device capable of monitoring the energy consumed by a household device. From this information, a consumption profile is model to detect anomalies of operation, during operation, and to detect electrical faults.The prototype of the device is equipped with a current sensor and a communication module, which sends the data to a web application to record energy consumption. The processing of the information, to predict faults, is carried out in an artificial neuronal network with multi-layer architecture implemented in MATLAB.
AB - This paper presents the design of a device capable of monitoring the energy consumed by a household device. From this information, a consumption profile is model to detect anomalies of operation, during operation, and to detect electrical faults.The prototype of the device is equipped with a current sensor and a communication module, which sends the data to a web application to record energy consumption. The processing of the information, to predict faults, is carried out in an artificial neuronal network with multi-layer architecture implemented in MATLAB.
KW - consumption
KW - energy
KW - Internet of things
KW - neuronal network
UR - https://www.scopus.com/pages/publications/85075765749
U2 - 10.1109/ISGT-LA.2019.8895440
DO - 10.1109/ISGT-LA.2019.8895440
M3 - Contribución a la conferencia
AN - SCOPUS:85075765749
T3 - 2019 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT Latin America 2019
BT - 2019 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT Latin America 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT Latin America 2019
Y2 - 15 September 2019 through 18 September 2019
ER -