Review of Artificial Intelligence Systems in Electrical Engineering: Challenges and Solutions

Artificial intelligence (AI) has become an increasingly important component in the field of electrical engineering, offering a wide range of applications and solutions to complex problems. From smart grids to autonomous vehicles, AI technologies have the potential to revolutionize the way we design, operate, and maintain electrical systems. However, the integration of AI systems in electrical engineering also presents a number of challenges that need to be addressed in order to fully realize the benefits of this technology. One of the major challenges facing the implementation of AI in electrical engineering is the lack of data quality and availability. AI systems rely heavily on large amounts of high-quality data to train and improve their performance. In the context of electrical engineering, this can be particularly challenging due to the limited availability of real-world data, as well as the complexity and variability of electrical systems. Additionally, ensuring the security and privacy of sensitive data used by AI systems is another important consideration that needs to be carefully addressed. Another challenge facing the integration of AI in electrical engineering is the interpretability and exploitability of AI algorithms. Many AI systems, such as deep learning models, are often considered black boxes, making it difficult for engineers to understand how these models arrive at their decisions. In safety-critical applications, such as power grid control or autonomous vehicles, the lack of interpretability can be a major barrier to the adoption of AI technologies. Developing methods for explaining and interpreting the decisions made by AI systems is therefore crucial for ensuring the reliability and trustworthiness of these systems in electrical engineering applications. In order to address these challenges, researchers and engineers in the field of electrical engineering are actively working on developing new algorithms and techniques that improve the robustness, efficiency, and interpretability of AI systems. By leveraging advancements in machine learning, data analytics, and signal processing, the field of electrical engineering is poised to benefit from the transformative potential of AI technologies. With continued research and development, it is likely that AI systems will play an increasingly important role in shaping the future of electrical engineering.

کلیدواژه ها:

Artificial intelligence ، Electrical engineering ، Smart grids ، Autonomous Vehicles