Paper co-authored by AUI Ph.D. student Safae Bourhnane and faculty is published in MDPI Applied Sciences
Ph.D. student and faculty member Ms. Safae Bourhnane and Dr. Mohamed Riduan Abid, from the AUI School of Science and Engineering, recently published a paper titled "Cluster of Single-Board Computers at the Edge for Smart Grids" in the journal MDPI Applied Sciences. The paper has a JCR (Journal Citation Reports) Impact Factor of 2.67. The paper was accepted for publication on the 15th of November, 2021, and published on the 19th of November. The piece was a collaboration with Khalid Zinedine from the Faculty of Sciences at Mohammed V University of Rabat; Najib Elkamoun, from the Faculty of Sciences El Jadida at Chouaib Doukkali University; and Driss Benhaddou, from the School of Engineering and Technology at the University of Houston. The study was funded by a US-NAS/USAID grant.
The paper reports on an experiment conducted by the authors on the benefits of using single-board computers (SBCs) for smart grids. Electric grids are the network that allow for electricity to be provided over a region of land. A smart grid, on the other hand, has the advantage that it collects data on the user and is able to integrate renewable energy. Therefore, smart grids allow users to know more about their own consumption between them and the service. The authors considered using the simpler SBCs because, among their many benefits, they do not have space for other components to be added, so it causes less bugs – therefore, their use is more straightforward. Edge computing refers to storing data outside a centralized location, such as directly where the data is generated, making it more time-efficient in sending information from one place to another. In an attempt to determine the most efficient method, the authors used SBCs such as Raspberry Pi 3 Model B, Raspberry Pi 3 Model B+, and Odroid C2, but since they have limited computing ability, they realized that clustering them in a Pi Stack at the edge resulted in higher computing power.
More details about the paper can be found at https://www.mdpi.com/2076-3417/11/22/10981.