ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY IN NORTH AFRICA: INNOVATING SMART CITIES
DOI:
https://doi.org/10.70672/a17nw054Keywords:
Smart cities, Smart grids, optimization, Machine learning, Artificial Intelligence, Renewable Energy, Energy Sector, InnovationAbstract
One of the most promising research areas for future smart cities is the field of smart energy. Critical issues related to optimisation, the establishment of adaptive smart grids, and advanced computational techniques enabled by artificial intelligence and machine learning warrant further exploration. Renewable energies (RE) are a major asset for global development in the face of climate change and resource scarcity. Artificial intelligence (AI) offers innovative approaches to organizing activities in response to these ever-changing needs. By integrating AI, we can improve the design, deployment and production of RE infrastructures, addressing multiple challenges and boosting the sector's growth and resilience. Our aim is to explore how AI can optimize renewable energy processes in North Africa, assess its impact on different energy sources, analyze labor productivity in the renewable energy sector and discuss its implications for the future development of smart cities.
References
[1] Usman, F. O., Ani, E. C., Ebirim, W., Montero, D. J. P., Olu-lawal, K. A., & Ninduwezuor-Ehiobu, N. (2024). Integrating renewable energy solutions in the manufacturing industry: challenges and opportunities: a review. Engineering Science & Technology Journal, 5(3), 674-703.
[2] Radwan, A. (2018). Science and innovation policies in North African Countries: Exploring challenges and opportunities. Entrepreneurship and Sustainability Issues, 6(1), 268-282.
[3] Trevisan, R., Ghiani, E., & Pilo, F. (2023). Renewable Energy Communities in Positive Energy Districts: A Governance and Realisation Framework in Compliance with the Italian Regulation. Smart Cities, 6(1), 563-585.
[4] Lu, Y., Khan, Z. A., Alvarez-Alvarado, M. S., Zhang, Y., Huang, Z., & Imran, M. (2020). A critical review of sustainable energy policies for the promotion of renewable energy sources. Sustainability, 12(12), 5078.
[5] Hassan, Q., Viktor, P., Al-Musawi, T. J., Ali, B. M., Algburi, S., Alzoubi, H. M., ... & Jaszczur, M. (2024). The renewable energy role in the global energy Transformations. Renewable Energy Focus, 48, 100545.
[6] Hamdan, A., Ibekwe, K. I., Ilojianya, V. I., Sonko, S., & Etukudoh, E. A. (2024). AI in renewable energy: A review of predictive maintenance and energy optimization. International Journal of Science and Research Archive, 11(1), 718-729.
[7] Binyamin, S. S., Slama, S. A. B., & Zafar, B. (2024). Artificial intelligence-powered energy community management for developing renewable energy systems in smart homes. Energy Strategy Reviews, 51, 101288.
[8] Blasch, E., Pham, T., Chong, C. Y., Koch, W., Leung, H., Braines, D., & Abdelzaher, T. (2021). Machine learning/artificial intelligence for sensor data fusion–opportunities and challenges. IEEE Aerospace and Electronic Systems Magazine, 36(7), 80-93.
[9] Hemamalini, V., Mishra, A. K., Tyagi, A. K., & Kakulapati, V. (2024). Artificial Intelligence–Blockchain‐Enabled–Internet of Things‐Based Cloud Applications for Next‐Generation Society. Automated Secure Computing for Next‐Generation Systems, 65-82.
[10] Lin, K., Li, Y., Zhang, Q., & Fortino, G. (2021). AI-driven collaborative resource allocation for task execution in 6G-enabled massive IoT. IEEE Internet of Things Journal, 8(7), 5264-5273.
[11] Kanungo, S. (2024). AI-driven resource management strategies for cloud computing systems, services, and applications. World Journal of Advanced Engineering Technology and Sciences, 11(2), 559-566.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Malaysian Journal of Industrial Technology
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Journal of Engineering Technology (JET) is an open-access journal that follows the Creative Commons Attribution-Non-commercial 4.0 International License (CC BY-NC 4.0)
