Embedded Artificial Intelligence and the Internet of Things for Photovoltaic Systems

• Explains how to apply embedded AI techniques and their advantages in solving challenging real-world problems in photovoltaic systems
• Bridges the gap between laboratory-scale research and industrial applications by designing end-to-end prototypes to address key problems in PV systems
• Provides guidance on implementing and deploying TinyML on edge devices, such as MCUs, CPUs, and GPUs, with various case studies in this field

Adel Mellit is a Professor at the Faculty of Sciences and Technology, University of Jijel, Algeria, and a Senior Associate Member at the International Centre of Theoretical Physics (ICTP), Trieste, Italy. He was previously the Director of the Renewable Energy Laboratory at University of Jijel. Prof. Mellit’s research focuses on the application of AI techniques, including deep learning and TinyML, in solar photovoltaic systems. He has authored or co-authored over 200 papers in international peer reviewed journals and numerous papers in conference proceedings, and has acted as editor of various conference proceedings. He is an Editor of the IEEE Journal of Photovoltaics, Subject Editor of the Energy journal (Elsevier) and an editorial board member of the Renewable Energy journal (Elsevier). He co-authored the Handbook of Artificial Intelligence Techniques in Photovoltaic Systems: Modelling, Control, Optimization, Forecasting, and Fault Diagnosis, published by Elsevier under the Academic Press imprint in 2022.