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Bekkay / Mellit / Amine Koulali

Proceedings of the 3rd International Conference on Electronic Engineering and Renewable Energy Systems

ICEERE 2022, 20 -22 May 2022, Saidia, Morocco

Medium: Buch
ISBN: 978-981-19-6299-8
Verlag: Springer Nature Singapore
Erscheinungstermin: 13.04.2024
Lieferfrist: bis zu 10 Tage

This book includes papers presented at the 3rd International Conference on Electronic Engineering and Renewable Energy (ICEERE 2022), which focus on the application of artificial intelligence techniques, emerging technology and the Internet of things in electrical and renewable energy systems, including hybrid systems, micro-grids, networking, smart health applications, smart grid, mechatronics and electric vehicles. It particularly focuses on new renewable energy technologies for agricultural and rural areas to promote the development of the Euro-Mediterranean region. Given its scope, the book is of interest to graduate students, researchers and practicing engineers working in the fields of electronic engineering and renewable energy.


Produkteigenschaften


  • Artikelnummer: 9789811962998
  • Medium: Buch
  • ISBN: 978-981-19-6299-8
  • Verlag: Springer Nature Singapore
  • Erscheinungstermin: 13.04.2024
  • Sprache(n): Englisch
  • Auflage: 2023
  • Serie: Lecture Notes in Electrical Engineering
  • Produktform: Kartoniert
  • Gewicht: 1958 g
  • Seiten: 1083
  • Format (B x H x T): 155 x 235 x 59 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

Smart Renewable Energy Systems and decarbonisation.- Internet of Things: Applications, Enablers, Security.- One-dimensional photonic crystals: Fondamentals and applications.- Health Monitoring Systems for the Renewable Energy.- Energy performances of a photovoltaic thermal plant using different.- New methods developed for precision agriculture.- Image blur control benefits to visual servo control in robotics.- Agrivoltaics: novel systems to optimize the food water energy nexus.- Fault Detection and Diagnosis applied to photovoltaic power plants.- Machine Learning for Analog Circuits Design.