Review Process to Investigate Trends of Using Arduino to Enhance AI Study

Abstract

In the industrial sector, Artificial Intelligence (AI) technology has been extensively utilized and integrated into educational curricula and teaching methodologies to enhance educational effectiveness and respond to the needs of entrepreneurs. However, due to its costliness, more learning tools and technology are needed to ensure AI education. The Arduino board offers a user-friendly and cost- effective solution that enables the study of complex applications involving the integration of artificial intelligence with Arduino programming. This study presents a review process to investigate trends of using Arduino to enhance AI study. This study highlights the increasing complexity of using Arduino boards with artificial intelligence algorithms. Specifically, it explores their applications in domains such as multiple linear regression (MLR), particle swarm optimization (PSO), adaptive neuro-fuzzy inference systems (ANFIS), and Node-RED. The findings of this study will serve as a valuable reference for scholars interested in this domain and as a guide for AI education in the future.