Digital Signals Processing and Digital devices in smart energy management systems
Mentor: Javier Castillo Villar
Phone: (+34) 916647499
University: Universidad Rey Juan Carlos
Partner Host Institution: N.A.
Keywords: Smart energy management systems, compressive sampling, Smart Grid, Security, Big data, High Performance Computing

Digital Signals Processing and Digital devices in smart energy management systems

Recent advances in signal processing algorithms and digital signal processors have allowed to implement many digital applications. These advances can be applied to energy management systems. These systems need to process enormous amounts of information in order to identify various problems and make management decisions more accurate.
Technological advances in embedded digital systems have allowed energy management systems to use digital devices for the acquisition, processing and visualization of information. On the other hand, an intelligent system demands the execution of more complex and robust processes.
In this line of research, we will study the design of embedded digital systems and processing algorithms, aimed at supporting smart energy management processes

Departament: Computing Science, Computer Architecture, Programming Languages and Systems and Statistics and Operative Investigation
Research Group: GDHwSw
More Information:
Relevants projects on the area: Project name: Context & Inteligence, Sponsor: Ministerio de economía y competitividad, Ref: IPT-2012-0912-4300000, Duration: 01/05/2012 – 31/12/2014, Main Researcher: David Ríos
Relevants publications on the area: 1.- Autor: Jeison Marín Alfonso, Jose Ignacio Martínez Torre, Henry Arguello Fuentes, Leonardo Betancur Agudelo, Título: Compressive Multispectral Spectrum Sensing for Spectrum Cartography, Ref.: Sensors, Num , Vol: 18, Pag: 387-407, Fecha: 2018, ISSN: 1424-8220, DOI: 10.3390/s18020387, JCR 2017: 2,67
2.- Autor: Jeison Marín A. Jose I. Martinez T. Leonardo Betancur. Herny Arguello. Titulo: Compressive Multispectral Model for Spectrum Sensing in Cognitive Radio Networks. Ref: 25th European Signal Processing Conference (EUSIPCO). Pag: pp. 2575-2571. Fecha: 2017, ISSN: 2076-1465, ISBN: 978-0-9928626-7-1, doi: 10.23919/EUSIPCO.2017.8081675, Google Scholar index: 26, CORE 2017 Rating: B